y_pred=logreg.predict(X_test) One of the image classification results from the Logistic regression model implemented is shown below where the implemented model’s ability to correctly classify the ...

While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

List of errors are presented in tree diagrams which are usually used for regression and classification. Depending on the model proposed, we can choose a technique to evaluate. The paper discusses ...

This project implements a multi-class logistic regression model to classify Iris flower types. It uses Python libraries to load and prepare the Iris dataset, train the model, evaluate its accuracy, ...

Nevertheless, these models do not consider a statistical distribution of data, which is an important type of uncertainty. Data distribution serves as crucial information for designing an optimal ...

The techniques mentioned in this notebook apply not only to classification problems, but to regression problems and problems dealing ... and properties of the Multilayer Perceptron (MLP) model, an ...

we propose an LGD estimation model using a two- stage model, classification tree-based boosting and support vector regression (SVR). We compare the proposed model’s predictive performance with ...