Creator : Sathya Krishnan Suresh

This is a python package to quicken the modelling and data analysis process.

PyPi : https://pypi.org/project/mb-scripts/

1. feature selection
   Feature selection sub-package has been added which consists of UnivariateFeatureSelection and CombinationFeatureSelection.
2. generate_time_series
   This function can be used to test out new Recurrent Neural Architectures.
3. Plotting feature importances using RandomForest
   This function helps selecting the features that are most correlated with the target variable with the help of RandomForest
4. Decomposition
   The new model in 🔥Decomposition🔥 contains standard decomposition methods that help with dimensionality reduction.
5. metrics update
   A lot of regression metrics have been added along with multiclass precision metrics variations.

The package can be downloaded using

pip install mb-scripts==<latest_version>

Latest version : 0.1.0.

Once you have installed mb_scripts you can begin using it.

Here are some examples for using mb_scripts.

train_validation_curve_for_rf - used to monitor RandomForestClassifier's overfitting

plot_decision_boundary is used to visually look at the decision boundary of classification functions



classifiers_metrics returns a dataframe that consists of precision, recall, accuracy_score and f1_score for all the classification models passed.

I am writing scripts regularly so the versions will keep changing for the next one month. Stay tuned.