Confusion Matrix for Classification Model Evaluation A confusion matrix is a n x n matrix used to describe the performance of a classification model (where n is the number of labels). In the confusion matrix, each row represents an actual class, while each column represents a predicted class.
Top Logistic Regression Classification Algorithms in Machine Learning:
The Decision Tree
Vector Machines should be used.
The quality of a statistical or machine learning model is measured using evaluation metrics. Any project requires the evaluation of machine learning models or algorithms. There are numerous evaluation measures available for testing a model.
The Classification method is a Supervised Learning technique that uses training data to identify the category of new observations. A software in Classification learns from a given dataset or observations and then classifies additional observations into one of several classes or groupings.