Regression
Support Vector Machine In Regression
Support Vector Machine In Regression Description The Support Vector Machine (SVM) approach for regression is a machine learning technique that seeks to identify a hyperplane that closely resembles the regression function. It reduces deviations ...
Ridge Regression
Ridge Regression Description Predict and analyze data points as output for multiple regression data that suffer from multicollinearity by controlling the magnitude of coefficients to avoid over-fitting. Why to use Predictive Modeling When to use To ...
Polynomial Regression
Polynomial Regression Description Polynomial Regression is a supervised learning method in which the relationship between the independent and dependent variables is modeled as an nth degree polynomial. Why to use Predictive Modeling When to use When ...
Random Forest Regression
Random Forest Regression Description Random Forest Regression is an ensemble learning method that combines multiple decision trees to create a powerful predictive model for continuous target variables. It utilizes random feature selection to improve ...
Poisson Regression
Poisson Regression Description Poisson Regression is a type of linear regression used to model the countable data. Why to use For regression analysis of count data When to use For numerical variables When not to use For textual variables ...
MLP (Multi-Layer Perceptron) Neural Network in Regression
MLP (Multi-Layer Perceptron) Neural Network in Regression Description An MLP neural network for regression is designed to predict continuous numerical values. It consists of multiple layers, including an input layer, one or more hidden layers, and an ...
Linear Regression
Regression is predictive modeling. It is a statistical method used in finance, investment, and other disciplines that attempts to determine the strength and character of the relationship between one dependent variable (usually denoted by Y) and a ...
Lasso Regression
Lasso Regression Description Lasso Regression is used to penalize the regression method to select a subset of variables by imposing a constraint on model parameters. Why to use Predictive Modeling When to use For variables having high ...
k Nearest Neighbor Regression
k Nearest Neighbor Regression Description k Nearest Neighbor (KNN) Regression enables you to predict new data points based on the known classification of other points. In kNN, we take a bunch of labeled points and then learn how to label other ...
Extreme Gradient Boost Regression (XGBoost)
Extreme Gradient Boost Regression (XGBoost) Description Extreme Gradient Boost (XGBoost) Regression is a Decision tree-based ensemble algorithm that uses a gradient boosting framework. Why to use Predictive Modeling When to use When high execution ...
Decision Tree Regression
Decision Tree Regression Description Decision Tree Regressor builds a regression model in the form of a tree structure where each leaf node represented a class or a decision. Why to use When you want to predict a value depending on single or multiple ...
Regression
Regression is predictive modeling. It is a statistical method, used in finance, investment, and other disciplines, that attempts to determine the strength and character of the relationship between one dependent variable (usually denoted by Y) and a ...