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Machine Learning
Machine Learning
Delve into the heart of OTASAI's visual machine learning capabilities. Design, train, and deploy models visually, eliminating the need for complex coding. Unleash the potential of machine learning with simplicity at its core.
Machine learning overview
Logistic Regression parameters
Naive Bayes GaussianNB parameters
Naive Bayes BernoulliNB parameters
Naive Bayes CategoricalNB parameters
Naive Bayes ComplementNB parameters
Naive Bayes MultinomialNB parameters
K-Nearest Neighbors (KNN) parameters
Decision Tree Classifier parameters
Support Vector Machines (SVM) parameters
Random Forest Classification parameters
Linear Regression parameters
Ridge Regression parameters
Lasso Regression parameters
Gradient Boosting parameters
Random Forest Regressor parameters
Decision Tree Regressor parameters
Support Vector Machines (SVM) Regressor parameters
Machine learning - status page
Training machine learning
Class-specific One-vs-Rest (OVR) Curve Chart
Micro-Average ROC Curve Chart
Macro-Average ROC Curve Chart
Feature Importance Chart
Heatmap for Confusion Matrix (All Classes) chart
Main Diagonal of Confusion Matrix chart
Heatmap Confusion Matrix for a Specific Class
Precision-Recall Curve Chart
Precision-Recall Curve Binary Chart
General Parameter Chart
Confusion Matrix Binary chart
Histogram Binary chart
Feature Importance Binary chart
Machine learning Results Page for classification
ROC Curve binary chart
Prediction vs Ground Truth chart
Residual plot
Feature Importance chart regression
Q-Q Plot
Standardized Residuals vs. Leverage Plot
Machine learning Results Page for regression
