jarvis.ai.pkgs.sklearn.classification
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Simple ML models for classifcation and regression.
Designed for educational purposes only
Module Contents¶
Functions¶
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Classifcation module for ROC curve for upto three classes. |
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Quickly train some of the classifcation algorithms in scikit-learn. |
Attributes¶
- jarvis.ai.pkgs.sklearn.classification.simple_class_models¶
- jarvis.ai.pkgs.sklearn.classification.classify_roc_ml(X=[], y=[], classes=[0, 1, 2], names=['High val', 'Low val', ''], n_plot=1, method='', preprocess=True, plot=False, test_size=0.1)[source]¶
Classifcation module for ROC curve for upto three classes.
It can be expanded in more classes as well. Args:
X: input feature vectors
y: target data obtained from binary_class_dat
classes: dummy classes
names: name holders for the target data
method: ML method
preprocess: whether to apply standard preprocessing techniques
plot: whether to plot the ROC curve