Metadata-Version: 2.1
Name: sklearning
Version: 0.0.1
Summary: metrics module
Home-page: UNKNOWN
Author: Dereck Jos
Author-email: dereckjos12@gmail.com
License: MIT
Description: This module is used to get metrics of Machine Learning/Deep Learning Models.It consists of all sklearn.metrics and stats module methods.Using this module you can also use all all different distances obtained in metrics.pairwise.cosine_distance etc.
        
        from sklearning.metrics import *
        
        y_test = [0,1,2,3,4]
        
        y_pred = [0,1,2,3,5]
        
        #Root Mean Squared Error
        
        rmse = rootMeanSquaredError(y_test,y_pred)
        
        print(rmse)
        
        o/p:0.4472135954999579
        
        
        
        #Regressor Summary
        
        summary = regressorSummary(y_test,y_pred)
        
        print(summary)
        
        #Stats Value
        
        statsValue(y_test,y_pred)
        
        o/p:
        
        statsValue(y_test,y_pred)
        
        pvalues
        
         [0.53047777 0.00190127]
        
        tvalues
        
         [-0.70710678 10.39230485]
        
        rsquared
        
         0.972972972972973
        
        rsquared_adj
        
         0.963963963963964
        
        
        #All methods of sklean.metrics can be used by just giving the name of methods ex:
        
        mse = mean_squared_error(y_test,y_pred)
        
        print(mse)
        
        o/p: 0.2
Keywords: metrics
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Education
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
