Breaking News: Grepper is joining You.com. Read the official announcement!

Function to plot a grouped bar chart showing the training and validation results of the ML model in each fold after applying K-fold cross-validation. Parameters

Mert Bozkir answered on June 28, 2022 Popularity 1/10 Helpfulness 1/10

answer Function to plot a grouped bar chart showing the training and validation results of the ML model in each fold after applying K-fold cross-validation. Parameters

Function to plot a grouped bar chart showing the training and validation results of the ML model in each fold after applying K-fold cross-validation. Parameters

Comment

# Grouped Bar Chart for both training and validation data
def plot_result(x_label, y_label, plot_title, train_data, val_data):
        '''Function to plot a grouped bar chart showing the training and validation
          results of the ML model in each fold after applying K-fold cross-validation.
         Parameters
         ----------
         x_label: str, 
            Name of the algorithm used for training e.g 'Decision Tree'
          
         y_label: str, 
            Name of metric being visualized e.g 'Accuracy'
         plot_title: str, 
            This is the title of the plot e.g 'Accuracy Plot'
         
         train_result: list, array
            This is the list containing either training precision, accuracy, or f1 score.
        
         val_result: list, array
            This is the list containing either validation precision, accuracy, or f1 score.
         Returns
         -------
         The function returns a Grouped Barchart showing the training and validation result
         in each fold.
        '''
        
        # Set size of plot
        plt.figure(figsize=(12,6))
        labels = ["1st Fold", "2nd Fold", "3rd Fold", "4th Fold", "5th Fold"]
        X_axis = np.arange(len(labels))
        ax = plt.gca()
        plt.ylim(0.40000, 1)
        plt.bar(X_axis-0.2, train_data, 0.4, color='blue', label='Training')
        plt.bar(X_axis+0.2, val_data, 0.4, color='red', label='Validation')
        plt.title(plot_title, fontsize=30)
        plt.xticks(X_axis, labels)
        plt.xlabel(x_label, fontsize=14)
        plt.ylabel(y_label, fontsize=14)
        plt.legend()
        plt.grid(True)
        plt.show()

Popularity 1/10 Helpfulness 1/10 Language whatever

Source: www.section.io

Tags: bar-chart each fold function k-fold ml model parameters plot training validation whatever

Link to this answer
Share Copy Link

Contributed on Jun 28 2022

Mert Bozkir

0 Answers Avg Quality 2/10

Function to plot a grouped bar chart showing the training and validation results of the ML model in each fold after applying K-fold cross-validation. Parameters

Contents

More Related Answers

Function to plot a grouped bar chart showing the training and validation results of the ML model in each fold after applying K-fold cross-validation. Parameters

Grepper

Documentation

Social

Legal

Contact

Oops, You will need to install Grepper and log-in to perform this action.