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### Analysis of accuracy checking Algorithms:

|Algorithm|Available JS Libraries|Notes|Link/Ref.| |
|-|-|-|-|-|
|Root Mean Square Error(RMSE)|https://www.npmjs.com/package/rmse|Need to integrate it with CSV file by extracting the array from a CSV column|https://www.statisticshowto.com/probability-and-statistics/regression-analysis/rmse-root-mean-square-error/|http://statweb.stanford.edu/~susan/courses/s60/split/node60.html|
|Mean F-Score|https://www.npmjs.com/package/fscore|Need to integrate it with CSV file by extracting the array from a CSV column|https://en.wikipedia.org/wiki/F-score| |
|Mean Squared Error(MSE)|https://www.npmjs.com/package/mse|Library is not widely used, can be implemented using python pandas, numpy, scikit libs. Need to implement using the formula|https://www.geeksforgeeks.org/python-mean-squared-error/| |
|Mean Squared Logarithmic Error(MSLE)|Not Available|Need to implement or need to use the library from python sklearn|https://peltarion.com/knowledge-center/documentation/modeling-view/build-an-ai-model/loss-functions/mean-squared-logarithmic-error-(msle)|https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_log_error.html|
|Root Mean Squared Logarithmic Error(RMSLE)|Not Available|Can be implemented using python sklearn with some additional codes|https://scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_log_error.html| |
|Absolute Error(AE)| |Need to implement|https://www.statisticshowto.com/absolute-error/| |
|Mean Absolute Error(MAE)|https://www.npmjs.com/package/mae|library is not widely used|https://www.statisticshowto.com/absolute-error/| |




**Note:** No single library found that contains all the error checking algorithms in one place, not in javascript, not even in python. We need to do some study on statistics topics to understand the theory and formulas to implement those functions. In python pandas, there are some built-in functions such as MEAN, MEAN DEVIATION, SQUARED MEAN DEVIATION, etc. that works with CSV sheets. We may need to write some wrapper function to prepare custom accuracy checking algorithms, in python. But for javascript, we can use panda.js or danfo.js which are python pandas equivalent js libraries, again we have to write some codes and wrapper to get them workable.


### Analysis on various libraries and their alternatives, usecases:

|python libraries|equivalent javascript libraries|Note|Link/Ref.|
|-|-|-|-|
|pandas|panda.js| |https://stratodem.github.io/pandas.js-docs/#introduction|
|pandas|danfo.js| |https://blog.tensorflow.org/2020/08/introducing-danfo-js-pandas-like-library-in-javascript.html|
|scikit-learn(sk-learn)|scikit-learn|Not maintained anymore|https://www.npmjs.com/package/scikit-learn|
| | | | |
|matplotlib|D3.js| |https://d3js.org/|
|matplotlib|mpld3| |https://mpld3.github.io/|
|matplotlib|nodeplotlib| | |
|matplotlib|matplotnode| | |



**Note:** An elaborative discussion on multiple various libs with their various features,  https://stackoverflow.com/a/43825646/2060243

