- ML Introduction
- ML Logistic Regression
- ML Linear Regression
- ML Data Clustering
- ML Categorical Data
- ML Decision Tree
- ML K-Means
- ML KNN
- ML Linear Graph
- ML Data Cleaning
- ML Data Distribution
- ML Standard Deviation
- ML Scatter Plot
- ML Polynomial Regression
- ML Confusion Matrix
- ML K Nearest Neighbor
- ML Training
- ML Data Distribution
- ML Classification Regression
- ML Random Forest
- ML Deployment
- ML Deep Learning
- ML Reinforcement Learning
- ML Dimensionality Reduction
- ML Neural Network
ML Confusion Matrix.
In machine learning, Classification is used to split data into categories. But after cleaning and preprocessing the data and training our model, how do we know if our classification model performs well? That is where a confusion matrix comes into the picture.
A confusion matrix is used to measure the performance of a classifier in depth.