How to use Regression Metrics in Python Regression Metrics are a set of techniques used to evaluate the performance of a regression model, which is a type of machine learning model that is used to predict a continuous numerical value. These metrics provide a way to measure the accuracy and other aspects of a model’s …
Day: February 16, 2019
How to use Classification Metrics in Python Classification Metrics are a set of techniques used to evaluate the performance of a classifier. These metrics provide a way to measure the accuracy, precision, recall and other aspects of a classifier’s performance. They are widely used in machine learning to evaluate the effectiveness of a model and …
How to visualise Decision Tree Model – Multiclass Classification in Python A Decision Tree is a popular machine learning model that is used for both classification and regression tasks. It works by breaking down a dataset into smaller and smaller subsets, while at the same time an associated decision tree is incrementally developed. One of …
How to classify “wine” using different Boosting Ensemble models e.g. XgBoost, CatBoost, LightGBM – Multiclass Classification in Python Boosting is a popular machine learning technique that is often used to improve the performance of a classifier. A boosting algorithm combines the predictions of multiple simpler models to make a more accurate final prediction. In this …