# Vline delay time histogram prediction result

* For each corridor, **20** experiments on the same data set are run.
* Each experiment consists for 80% of the data for training and the remaining 20% for testing.
* The first 20 results of each corridor are shown on the tables below.
* All numbers less than $10^{-5}$ are regarded as $0.0$.
* 5 columns: `[less_5, btw_5_10, btw_10_15, btw_15_20, more_20]`

---

# MSE - vline delay time prediction (slippery)
## data/slippery/Eastern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.200e-05 -2.035e-03 0.000e+00] | 4.0121e-06 |
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.200e-05 -1.114e-02 0.000e+00] | 0.0001234 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 3.200e-05 2.871e-03 0.000e+00] | 8.423e-06 |
| [0. 0. 0. 0. 0.] | [ 0.0000e+00 0.0000e+00 3.2000e-05 -1.1111e-02 0.0000e+00] | 0.00012276 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 1.37872e-01 0.00000e+00] | 0.019018 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 3.200e-05 4.986e-03 0.000e+00] | 2.5182e-05 |
| [0. 0. 0. 0. 0.] | [0.00e+00 0.00e+00 3.20e-05 7.75e-02 0.00e+00] | 0.0060111 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 3.81699e-01 0.00000e+00] | 0.14572 |
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.200e-05 -3.128e-03 0.000e+00] | 9.5854e-06 |
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.200e-05 -3.739e-03 0.000e+00] | 1.3743e-05 |
| [0. 0. 1. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 1.56028e-01 0.00000e+00] | 0.71224 |
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.200e-05 -3.295e-03 0.000e+00] | 1.0647e-05 |
| [0. 0. 0. 0. 0.] | [ 0. 0. 0.411182 -0.001742 0. ] | 0.16764 |
| [0. 0. 0. 0. 0.] | [ 0.00e+00 0.00e+00 3.20e-05 -2.13e-04 0.00e+00] | 3.3036e-08 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 1.56283e-01 0.00000e+00] | 0.024434 |
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.200e-05 -6.127e-03 0.000e+00] | 3.7153e-05 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 3.200e-05 6.099e-03 0.000e+00] | 3.759e-05 |
| [0. 0. 0. 2. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 6.08537e-01 0.00000e+00] | 1.9361 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 3.200e-05 7.509e-03 0.000e+00] | 5.6855e-05 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 4.21718e-01 0.00000e+00] | 0.17787 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0.02833 0.13542 0. ] | 0.03275 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 8.00000 47.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 11.06727 53.86070 0.00000 ]`|

**MSE_col** = 0.03274962576967501
**MSE_row** = 0.15733133212803624

## data/slippery/NE.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0. 0.] | 0.0 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0. 0. 0.] | 0.00000 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 0.00000 0.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 0.00000 0.00000 0.00000 ]`|

**MSE_col** = 0.0
**MSE_row** = 0.0

## data/slippery/Northern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0. 0. 0.821564 1.535711 0. ] | 5.5567 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 5.90000e-05 1.12061e-01 0.00000e+00] | 0.012571 |
| [0. 0. 0. 2. 0.] | [0. 0. 0.001357 0.420684 0. ] | 2.49 |
| [0. 0. 0. 0. 0.] | [ 0.0000e+00 0.0000e+00 -5.5000e-05 2.6691e-02 0.0000e+00] | 0.0007095 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 1.100e-05 5.532e-03 0.000e+00] | 3.0724e-05 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.10000e-05 2.83395e-01 0.00000e+00] | 0.08033 |
| [0. 0. 0. 0. 0.] | [ 0.000e+00 0.000e+00 3.500e-05 -3.552e-03 0.000e+00] | 1.2369e-05 |
| [0. 0. 0. 1. 0.] | [ 0. 0. -0.000272 -0.010493 0. ] | 1.0216 |
| [0. 0. 0. 0. 0.] | [ 0. 0. 0.000112 -0.026888 0. ] | 0.00071698 |
| [0. 0. 0. 0. 0.] | [ 0. 0. 0.000149 -0.054578 0. ] | 0.0029626 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.000582 0.121959 0. ] | 0.015016 |
| [0. 0. 0. 0. 0.] | [ 0. 0. 0.000327 -0.056794 0. ] | 0.0031885 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.10000e-05 1.63512e-01 0.00000e+00] | 0.026746 |
| [0. 0. 0. 1. 0.] | [ 0. 0. 0.002789 -0.018349 0. ] | 1.0314 |
| [0. 0. 0. 0. 0.] | [ 0.0000e+00 0.0000e+00 -5.5000e-05 -6.7849e-02 0.0000e+00] | 0.0046109 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.000446 0.009644 0. ] | 0.0001018 |
| [0. 0. 0. 0. 0.] | [0.0000e+00 0.0000e+00 5.9000e-05 3.7405e-02 0.0000e+00] | 0.0014036 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 3.500e-05 5.532e-03 0.000e+00] | 3.0993e-05 |
| [0. 0. 0. 0. 0.] | [ 0.0000e+00 0.0000e+00 -1.7000e-05 1.6234e-01 0.0000e+00] | 0.026349 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.000138 0.01129 0. ] | 0.00013059 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0.0466 0.22102 0. ] | 0.05353 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 9.00000 70.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 19.25302 62.59162 0.00000 ]`|

**MSE_col** = 0.05352570785315254
**MSE_row** = 0.2969612741673328

## data/slippery/SW.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6047e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6047e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| [0. 0. 0. 0. 0.] | [0.e+00 0.e+00 0.e+00 6.e-05 0.e+00] | 3.6074e-09 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0. 0.02551 0. ] | 0.00510 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 0.00000 13.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 0.00000 15.40556 0.00000 ]`|

**MSE_col** = 0.005102575082159645
**MSE_row** = 0.025512875410798143

## data/slippery/Western.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -1.04e-04 0.00e+00] | 9.5662e-10 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -3.62e-04 0.00e+00] | 8.3517e-08 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -5.69e-04 0.00e+00] | 2.4655e-07 |
| [0. 0. 0. 0. 0.] | [3.20000e-05 0.00000e+00 4.10000e-05 2.40261e-01 0.00000e+00] | 0.05776 |
| [0. 0. 0. 0. 0.] | [3.20e-05 0.00e+00 4.00e-05 2.11e-04 0.00e+00] | 7.9848e-08 |
| [0. 0. 0. 0. 0.] | [3.20e-05 0.00e+00 4.10e-05 6.33e-04 0.00e+00] | 4.9771e-07 |
| [0. 0. 0. 0. 0.] | [9.96988e-01 0.00000e+00 4.05176e-01 9.40000e-05 0.00000e+00] | 1.9663 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -3.88e-04 0.00e+00] | 9.9629e-08 |
| [0. 0. 0. 0. 0.] | [ 3.200e-05 0.000e+00 4.100e-05 -1.507e-03 0.000e+00] | 2.0581e-06 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -2.47e-04 0.00e+00] | 3.0253e-08 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -9.86e-04 0.00e+00] | 8.3344e-07 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -5.69e-04 0.00e+00] | 2.4655e-07 |
| [0. 0. 0. 0. 0.] | [ 3.200e-05 0.000e+00 4.100e-05 -2.195e-03 0.000e+00] | 4.505e-06 |
| [0. 0. 0. 0. 0.] | [3.20e-05 0.00e+00 4.10e-05 4.34e-04 0.00e+00] | 2.5661e-07 |
| [0. 0. 0. 0. 0.] | [3.20000e-05 0.00000e+00 4.02828e-01 2.91160e-02 0.00000e+00] | 0.1866 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 4.1e-05 2.5e-05 0.0e+00] | 9.5287e-09 |
| [0. 0. 0. 1. 0.] | [ 3.200e-05 0.000e+00 4.100e-05 -2.192e-03 0.000e+00] | 1.0042 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 4.10e-05 -3.58e-04 0.00e+00] | 8.1353e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 4.1e-05 8.9e-05 0.0e+00] | 2.6108e-08 |
| [0. 0. 0. 0. 0.] | [3.20e-05 0.00e+00 4.10e-05 8.36e-04 0.00e+00] | 8.2604e-07 |
| ... | ... | ... |
| **Col MSE** | [0.02183 0. 0.03234 0.0695 0. ] | 0.02474 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 1.00000 0.00000 11.00000 23.00000 0.00000 ]`|
|**Prediction** | `[ 12.19539 0.00000 6.87896 28.78761 0.00000 ]`|

**MSE_col** = 0.02473542270720551
**MSE_row** = 0.1371242760847758

---

# MSE - vline delay time prediction (overcrowding)
## data/overcrowding/Eastern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 3.23085e-01 0.00000e+00] | 0.45817 |
| [0. 0. 0. 1. 0.] | [0. 0. 0.384655 0.826952 0. ] | 0.044778 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 7.19064e-01 0.00000e+00] | 0.5171 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 5.17565e-01 0.00000e+00] | 0.23271 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 5.34826e-01 0.00000e+00] | 0.28607 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 9.06048e-01 0.00000e+00] | 0.0088209 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 8.04384e-01 0.00000e+00] | 0.038253 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 1.52583e-01 0.00000e+00] | 0.71806 |
| [0. 0. 0. 0. 0.] | [ 0.0000e+00 0.0000e+00 3.2000e-05 -3.4882e-02 0.0000e+00] | 0.0012146 |
| [0. 0. 0. 0. 0.] | [ 0.00000e+00 0.00000e+00 3.20000e-05 -1.00314e-01 0.00000e+00] | 0.010057 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 6.41804e-01 0.00000e+00] | 0.41195 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 6.17065e-01 0.00000e+00] | 0.14661 |
| [0. 0. 0. 2. 0.] | [0.0000e+00 0.0000e+00 3.2000e-05 5.5344e-01 0.0000e+00] | 2.0924 |
| [0. 0. 0. 2. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 4.12243e-01 0.00000e+00] | 2.5209 |
| [0. 0. 0. 1. 0.] | [ 0.0000e+00 0.0000e+00 3.2000e-05 -4.5907e-02 0.0000e+00] | 1.0939 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 3.20000e-05 5.08989e-01 0.00000e+00] | 0.24106 |
| [0. 0. 0. 1. 0.] | [0.000e+00 0.000e+00 3.200e-05 1.992e-03 0.000e+00] | 0.99596 |
| [1. 0. 0. 0. 0.] | [0.000000e+00 0.000000e+00 3.200000e-05 1.278096e+00 0.000000e+00] | 0.077355 |
| [0. 0. 0. 0. 0.] | [0.0000e+00 0.0000e+00 3.2000e-05 6.1373e-02 0.0000e+00] | 0.0037705 |
| [0. 0. 0. 1. 0.] | [0.0000e+00 0.0000e+00 3.2000e-05 3.0091e-02 0.0000e+00] | 0.94066 |
| ... | ... | ... |
| **Col MSE** | [0.00978 0. 0.02153 0.39072 0. ] | 0.08441 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 4.00000 0.00000 3.00000 262.00000 0.00000 ]`|
|**Prediction** | `[ 1.44194 0.00000 12.35792 260.39052 0.00000 ]`|

**MSE_col** = 0.0844072013885419
**MSE_row** = 0.36736887025458514

## data/overcrowding/NE.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 1. 0.] | [0. 0. 0. 1.037456 0. ] | 0.001403 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.923725 0. ] | 0.0058178 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.73747 0. ] | 0.068922 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.959582 0. ] | 0.0016336 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.206699 0. ] | 0.62933 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 1.050731 0. ] | 0.0025737 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.55314 0. ] | 0.30596 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.136286 0. ] | 0.018574 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.037455 0. ] | 0.92649 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.144982 0. ] | 0.73106 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.975561 0. ] | 0.00059728 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.063219 0. ] | 0.0039967 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.605737 0. ] | 0.36692 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 1.373729 0. ] | 0.13967 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.091428 0. ] | 0.8255 |
| [0. 0. 0. 0. 0.] | [ 0. 0. 0. -0.065105 0. ] | 0.0042386 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 0.097269 0. ] | 0.81492 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.647147 0. ] | 0.4188 |
| [0. 0. 0. 1. 0.] | [0. 0. 0. 1.167857 0. ] | 0.028176 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.052721 0. ] | 0.0027795 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0. 0.30219 0. ] | 0.06044 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 0.00000 284.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 0.00000 304.30049 0.00000 ]`|

**MSE_col** = 0.06043731297794562
**MSE_row** = 0.3021865648897279

## data/overcrowding/Northern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 1. 0.] | [0. 0. 0.015598 0.806434 0. ] | 0.031673 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.254688 0.660589 0. ] | 0.83773 |
| [0. 0. 0. 1. 0.] | [0. 0. 0.246658 0.991662 0. ] | 0.056796 |
| [0. 0. 0. 1. 0.] | [ 0. 0. -0.00153 0.316783 0. ] | 0.46888 |
| [0. 0. 0. 0. 0.] | [ 0. 0. -0.010037 0.541448 0. ] | 0.2824 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 0.00000e+00 6.61000e-04 9.25347e-01 0.00000e+00] | 0.0054748 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.000661 0.024945 0. ] | 0.00065568 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.007683 0.441524 0. ] | 0.20179 |
| [0. 0. 0. 1. 0.] | [0. 0. 0.124057 0.47668 0. ] | 0.15941 |
| [0. 0. 0. 1. 0.] | [0. 0. 0.081516 1.297169 0. ] | 0.1434 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.000351 0.076452 0. ] | 0.0058987 |
| [0. 0. 0. 0. 0.] | [ 0. 0. -0.0119 0.100398 0. ] | 0.0078319 |
| [0. 0. 0. 0. 0.] | [ 0. 0. -0.000954 0.088014 0. ] | 0.0075794 |
| [0. 0. 0. 1. 0.] | [0. 0. 0.088894 0.7352 0. ] | 0.030943 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.009248 0.612773 0. ] | 0.38691 |
| [0. 0. 0. 0. 0.] | [0. 0. 0.000546 0.139853 0. ] | 0.019712 |
| [0. 0. 0. 0. 0.] | [ 0. 0. -0.000107 0.008719 0. ] | 7.4178e-05 |
| [0. 0. 0. 1. 0.] | [ 0. 0. -0.002217 0.263287 0. ] | 0.54602 |
| [0. 0. 0. 1. 0.] | [ 0. 0. -0.010142 0.487754 0. ] | 0.27289 |
| [0. 0. 0. 0. 0.] | [0.000e+00 0.000e+00 8.100e-05 7.913e-03 0.000e+00] | 6.3911e-05 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0.03431 0.32948 0. ] | 0.07276 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 11.00000 237.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 12.78503 245.00113 0.00000 ]`|

**MSE_col** = 0.07275865222672684
**MSE_row** = 0.35058869888597205

## data/overcrowding/SW.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [ 9.70000e-04 0.00000e+00 -2.40000e-05 9.47049e-01 0.00000e+00] | 0.8987 |
| [0. 0. 0. 0. 0.] | [-5.19000e-04 0.00000e+00 -2.91600e-02 9.04664e-01 0.00000e+00] | 0.7656 |
| [0. 0. 0. 1. 0.] | [-0.001133 0. -0.010076 0.051271 0. ] | 0.92148 |
| [0. 0. 0. 0. 0.] | [ 0.00447 0. -0.002135 0.211397 0. ] | 0.045681 |
| [0. 0. 0. 1. 0.] | [-3.80000e-04 0.00000e+00 -1.06100e-03 8.12351e-01 0.00000e+00] | 0.035755 |
| [0. 0. 0. 0. 0.] | [0.030467 0. 0.21112 0.511928 0. ] | 0.56778 |
| [0. 0. 0. 2. 0.] | [ 1.17000e-04 0.00000e+00 -1.16600e-03 9.50778e-01 0.00000e+00] | 1.1031 |
| [0. 0. 0. 2. 0.] | [ 0.009861 0. -0.014437 0.299626 0. ] | 2.9069 |
| [0. 0. 0. 0. 0.] | [-0.001107 0. 0.101763 0.79043 0. ] | 0.79404 |
| [0. 0. 0. 1. 0.] | [0.0021 0. 0.027539 0.489355 0. ] | 0.23137 |
| [0. 0. 0. 1. 0.] | [-0.009546 0. 0.043273 0.373715 0. ] | 0.35112 |
| [0. 0. 0. 0. 0.] | [2.15000e-04 0.00000e+00 8.74380e-02 3.65777e-01 0.00000e+00] | 0.2056 |
| [0. 0. 0. 1. 0.] | [ 6.30000e-05 0.00000e+00 -4.45500e-03 9.63607e-01 0.00000e+00] | 0.0016635 |
| [0. 0. 0. 1. 0.] | [ 0.002237 0. -0.00201 0.504498 0. ] | 0.2453 |
| [0. 0. 0. 0. 0.] | [ 0.236194 0. -0.003953 0.743158 0. ] | 0.9514 |
| [0. 0. 0. 2. 0.] | [ 0.123937 0. -0.000911 0.39512 0. ] | 2.1959 |
| [0. 0. 0. 1. 0.] | [-0.002375 0. -0.011204 0.720726 0. ] | 0.085763 |
| [0. 0. 0. 0. 0.] | [0.199237 0. 0.567694 0.707833 0. ] | 2.1749 |
| [0. 0. 0. 1. 0.] | [1.86337e-01 0.00000e+00 1.96000e-04 6.65270e-01 0.00000e+00] | 0.021962 |
| [0. 0. 0. 1. 0.] | [0.0679 0. 0.000516 0.491473 0. ] | 0.1937 |
| ... | ... | ... |
| **Col MSE** | [0.03667 0. 0.12853 0.36279 0. ] | 0.10560 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 9.00000 0.00000 21.00000 338.00000 0.00000 ]`|
|**Prediction** | `[ 14.42004 0.00000 39.50558 309.67898 0.00000 ]`|

**MSE_col** = 0.10559815478087875
**MSE_row** = 0.510016262268653

## data/overcrowding/Western.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 1. 0.] | [ 0.000000e+00 3.200000e-05 -9.882000e-03 1.526081e+00 0.000000e+00] | 0.26649 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 3.20000e-05 8.87772e-01 2.84577e-01 0.00000e+00] | 0.029715 |
| [0. 0. 0. 1. 0.] | [ 0.00000e+00 3.20000e-05 -3.08100e-03 7.91174e-01 0.00000e+00] | 0.044891 |
| [0. 0. 0. 1. 0.] | [ 0.000000e+00 3.200000e-05 -2.225000e-03 1.925674e+00 0.000000e+00] | 0.85282 |
| [0. 0. 0. 1. 0.] | [0. 0.005241 0.358341 0.299783 0. ] | 0.11332 |
| [0. 0. 1. 2. 0.] | [ 0.000000e+00 3.200000e-05 -1.272700e-02 1.987724e+00 0.000000e+00] | 1.0506 |
| [0. 0. 0. 1. 0.] | [ 0.00000e+00 3.20000e-05 -2.60000e-03 6.71551e-01 0.00000e+00] | 0.10957 |
| [0. 0. 0. 1. 0.] | [0.000000e+00 3.200000e-05 3.786000e-02 1.039819e+00 0.000000e+00] | 0.0060389 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 3.20000e-05 1.32920e-02 6.70381e-01 0.00000e+00] | 0.46745 |
| [0. 0. 0. 1. 0.] | [0.00000e+00 3.20000e-05 2.60957e-01 7.48376e-01 0.00000e+00] | 8.77e-05 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 3.20000e-05 3.05340e-02 4.45909e-01 0.00000e+00] | 0.22703 |
| [0. 0. 0. 1. 0.] | [0.0000e+00 3.2000e-05 3.1060e-03 3.3065e-01 0.0000e+00] | 0.44384 |
| [0. 0. 0. 0. 0.] | [ 0.000000e+00 3.200000e-05 -1.932000e-03 1.027409e+00 0.000000e+00] | 1.0517 |
| [0. 0. 0. 1. 0.] | [0.000000e+00 3.200000e-05 2.034000e-03 1.078847e+00 0.000000e+00] | 0.0065468 |
| [0. 0. 0. 0. 0.] | [ 0.00000e+00 3.20000e-05 -5.43000e-04 2.88463e-01 0.00000e+00] | 0.082916 |
| [0. 0. 1. 0. 0.] | [0.00000e+00 3.20000e-05 7.31600e-03 7.86474e-01 0.00000e+00] | 0.042509 |
| [0. 0. 0. 0. 0.] | [ 0.00000e+00 3.20000e-05 -3.31980e-02 9.81449e-01 0.00000e+00] | 0.89924 |
| [0. 0. 0. 0. 0.] | [ 0.00000e+00 3.20000e-05 -3.13400e-03 5.85785e-01 0.00000e+00] | 0.33952 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 3.20000e-05 9.59560e-02 7.27272e-01 0.00000e+00] | 0.67776 |
| [0. 0. 0. 1. 0.] | [0.000000e+00 3.200000e-05 1.910800e-02 2.402994e+00 0.000000e+00] | 2.0225 |
| ... | ... | ... |
| **Col MSE** | [0. 0.0248 0.1013 0.58112 0. ] | 0.14144 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 6.00000 31.00000 285.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 7.73172 42.42746 297.76538 0.00000 ]`|

**MSE_col** = 0.14144346444151737
**MSE_row** = 0.6688958915967969

---

# MSE - vline delay time prediction (animal struck)
## data/animal_struck/Eastern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.219939 0. ] | 0.048373 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0. 0. 0. 0.12589 0. ] | 0.015848 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 3.2e-05 0.0e+00] | 1.0049e-09 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0. 0.00818 0. ] | 0.00164 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 0.00000 3.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 0.00000 2.91785 0.00000 ]`|

**MSE_col** = 0.0016353139334885363
**MSE_row** = 0.008176569667442535

## data/animal_struck/NE.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 0.00000e+00 5.60000e-05 1.74458e-01] | 0.030455 |
| [0. 0. 0. 1. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 0.9998 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 0.00000e+00 5.60000e-05 1.14518e-01] | 0.013127 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 0.00000e+00 5.60000e-05 4.00029e-01] | 0.16007 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 0.0e+00 5.6e-05 4.3e-05] | 9.8139e-09 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0. 0.04502 0.02594] | 0.01419 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 0.00000 13.00000 9.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 0.00000 21.58711 8.35443 ]`|

**MSE_col** = 0.014191967504618958
**MSE_row** = 0.06891506736586385

## data/animal_struck/Northern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [ 3.200e-05 0.000e+00 -4.430e-04 -5.092e-03 4.100e-05] | 2.9837e-05 |
| [0. 0. 0. 0. 0.] | [ 3.200e-05 0.000e+00 -4.430e-04 4.368e-03 4.100e-05] | 1.5979e-05 |
| [0. 0. 0. 0. 0.] | [ 3.20000e-05 0.00000e+00 -7.30000e-05 7.38002e-01 4.10000e-05] | 0.54465 |
| [0. 0. 0. 0. 0.] | [ 3.20000e-05 0.00000e+00 -1.12700e-03 9.42367e-01 4.10000e-05] | 0.88607 |
| [0. 0. 0. 0. 0.] | [3.200e-05 0.000e+00 3.994e-03 7.490e-04 4.100e-05] | 2.3192e-05 |
| [0. 0. 0. 0. 0.] | [3.20000e-05 0.00000e+00 7.36233e-01 8.94600e-03 4.10000e-05] | 0.5554 |
| [0. 0. 0. 0. 0.] | [ 3.2000e-05 0.0000e+00 1.9496e-01 -1.9940e-03 4.1000e-05] | 0.037264 |
| [0. 0. 1. 0. 0.] | [ 3.200e-05 0.000e+00 1.180e-04 -1.852e-03 4.100e-05] | 1.0033 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 -8.49e-04 0.00e+00 4.10e-05] | 5.9239e-07 |
| [0. 0. 0. 0. 0.] | [ 3.200000e-05 0.000000e+00 6.460000e-04 -7.895000e-03 1.170095e+00] | 1.3523 |
| [0. 0. 0. 0. 0.] | [3.20000e-05 0.00000e+00 4.99488e-01 0.00000e+00 4.10000e-05] | 0.24957 |
| [0. 0. 0. 0. 0.] | [ 3.20e-05 0.00e+00 -6.07e-04 9.32e-04 4.10e-05] | 1.5831e-07 |
| [0. 0. 0. 0. 0.] | [3.20000e-05 0.00000e+00 2.90000e-05 6.66995e-01 4.10000e-05] | 0.44502 |
| [0. 0. 0. 0. 0.] | [ 3.2000e-05 0.0000e+00 -1.2000e-04 8.0871e-01 4.1000e-05] | 0.65393 |
| [0. 0. 0. 0. 0.] | [ 0.167323 0. 0.246467 -0.004082 0.827366] | 1.5304 |
| [0. 0. 0. 0. 0.] | [ 3.200e-05 0.000e+00 -1.220e-04 6.219e-03 4.100e-05] | 3.8068e-05 |
| [0. 0. 0. 0. 0.] | [ 3.20000e-05 0.00000e+00 7.35688e-01 -3.20000e-04 4.10000e-05] | 0.54087 |
| [0. 0. 0. 0. 0.] | [3.2000e-05 0.0000e+00 3.2700e-04 8.0546e-01 4.1000e-05] | 0.64941 |
| [0. 0. 0. 0. 0.] | [ 3.200e-05 0.000e+00 -1.220e-04 2.125e-03 4.100e-05] | 4.3071e-06 |
| [0. 0. 0. 0. 0.] | [ 3.20000e-05 0.00000e+00 8.60261e-01 -6.05000e-03 4.10000e-05] | 0.7298 |
| ... | ... | ... |
| **Col MSE** | [0.01049 0. 0.13066 0.07364 0.06627] | 0.05621 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 2.00000 0.00000 25.00000 17.00000 6.00000 ]`|
|**Prediction** | `[ 6.11727 0.00000 22.52240 28.64545 19.09659 ]`|

**MSE_col** = 0.05621334912906145
**MSE_row** = 0.355101077121216

## data/animal_struck/SW.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 1.72016e-01 3.20000e-05 0.00000e+00] | 0.0296 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.00000e+00 0.00000e+00 4.22122e-01 3.20000e-05 0.00000e+00] | 0.17821 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| [0. 0. 0. 0. 0.] | [0.0e+00 0.0e+00 3.2e-05 3.2e-05 0.0e+00] | 4.0197e-09 |
| ... | ... | ... |
| **Col MSE** | [0. 0. 0.01954 0.00386 0. ] | 0.00468 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 0.00000 6.00000 1.00000 0.00000 ]`|
|**Prediction** | `[ 0.00000 0.00000 6.20977 1.84729 0.00000 ]`|

**MSE_col** = 0.004679161291664171
**MSE_row** = 0.023395794731670735

## data/animal_struck/Western.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [1. 0. 1. 1. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 8.9992 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| [0. 0. 0. 0. 0.] | [4.2e-05 0.0e+00 3.2e-05 3.2e-05 3.2e-05] | 1.8687e-08 |
| ... | ... | ... |
| **Col MSE** | [0.03781 0. 0.02516 0.04199 0.01067] | 0.02313 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 14.00000 0.00000 9.00000 11.00000 4.00000 ]`|
|**Prediction** | `[ 6.76740 0.00000 8.64588 11.92496 4.30526 ]`|

**MSE_col** = 0.02312611630863001
**MSE_row** = 0.24456869118316013

---

# MSE - vline delay time prediction (WOLO)
## data/WOLO/Eastern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 3.2e-05 4.1e-05 4.1e-05 3.2e-05] | 3.1663e-08 |
| ... | ... | ... |
| **Col MSE** | [1.042000e-02 1.042000e-02 1.232500e-01 1.082707e+01 1.371000e-02] | 2.19697 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 5.00000 5.00000 25.00000 173.00000 5.00000 ]`|
|**Prediction** | `[ 0.01141 0.01141 5.37411 7.43129 4.37875 ]`|

**MSE_col** = 2.1969730366234175
**MSE_row** = 14.287686225067427

## data/WOLO/NE.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [0.000000e+00 3.200000e-05 1.650656e+00 1.981768e+00 3.200000e-05] | 13.195 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.000000e+00 3.199400e-02 5.600000e-04 1.904756e+00 2.238900e-02] | 3.8404 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [ 0.0000e+00 3.2000e-05 5.7000e-05 -1.0929e-02 3.2000e-05] | 0.00011682 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.000000e+00 3.200000e-05 1.997353e+00 7.306114e+00 7.397550e-01] | 100.87 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [ 0.00e+00 3.20e-05 5.70e-05 -8.09e-04 3.20e-05] | 4.7441e-07 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| [0. 0. 0. 0. 0.] | [0.0e+00 3.2e-05 5.7e-05 0.0e+00 3.2e-05] | 1.4562e-08 |
| ... | ... | ... |
| **Col MSE** | [0. 0.01997 0.15384 3.76003 0.01936] | 0.79064 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 0.00000 4.00000 30.00000 162.00000 7.00000 ]`|
|**Prediction** | `[ 0.00000 6.59097 24.94509 86.42361 3.59039 ]`|

**MSE_col** = 0.7906380909833948
**MSE_row** = 5.397848210684286

## data/WOLO/Northern.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 2. 0.] | [3.200000e-05 0.000000e+00 1.998160e+00 3.731203e+00 3.794260e-01] | 16.882 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [ 0. 0. 4. 11. 0.] | [3.200000e-05 0.000000e+00 1.998160e+00 4.506917e+00 5.300000e-05] | 72.162 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| [0. 0. 0. 0. 0.] | [3.2e-05 0.0e+00 7.0e-05 2.5e-05 5.3e-05] | 3.204e-08 |
| ... | ... | ... |
| **Col MSE** | [0.00789 0. 0.19333 4.55923 0.06984] | 0.96606 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 2.00000 0.00000 46.00000 254.00000 12.00000 ]`|
|**Prediction** | `[ 3.79727 0.00000 49.61363 197.70345 24.10657 ]`|

**MSE_col** = 0.9660587484849378
**MSE_row** = 6.027007659828627

## data/WOLO/SW.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [ 0. 0. 7. 63. 0.] | [ 1.02227 0.370605 3.035541 40.342554 1.239306] | 575.51 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 3.2e-05 4.0e-05 5.4e-05 3.0e-05] | 3.4308e-08 |
| ... | ... | ... |
| **Col MSE** | [7.041000e-02 7.250000e-03 7.925800e-01 3.629697e+01 5.507000e-02] | 7.44446 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 9.00000 3.00000 86.00000 751.00000 6.00000 ]`|
|**Prediction** | `[ 6.09610 1.67777 60.81748 583.04787 13.48589 ]`|

**MSE_col** = 7.4444563699482655
**MSE_row** = 46.89561080982835

## data/WOLO/Western.csv
| Target | Prediction | Row MSE |
|-----------------|-------------------------------------------|-----------|
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [1.060784 0. 1.99814 3.546102 0. ] | 43.626 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [2. 1. 2. 2. 6.] | [1.114483 0. 0.260846 2.009023 0. ] | 92.461 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 0. 0. 0.] | [3.0e-05 0.0e+00 5.0e-05 4.1e-05 0.0e+00] | 1.444e-08 |
| [0. 0. 3. 7. 0.] | [1.434656 0. 1.99814 2.9947 0. ] | 12.763 |
| ... | ... | ... |
| **Col MSE** | [0.17747 0.01281 0.17604 2.09897 0.46344] | 0.58575 |

| | sum |
|----|----------|
|**Ground Truth** | `[ 30.00000 6.00000 56.00000 125.00000 36.00000 ]`|
|**Prediction** | `[ 13.61139 0.69004 55.24431 104.99143 4.46998 ]`|

**MSE_col** = 0.5857465307044125
**MSE_row** = 4.577301246655834