Tag Archives: scikit-learn

IRIS Flower Classification using SKLEARN DecisionTree Classifier with Grid Search Cross Validation

IRIS Flower Classification using SKLEARN DecisionTree Classifier with Grid Search Cross Validation     The IRIS flower is a popular example in the field of machine learning. It is a type of flower that has different variations, such as the setosa, virginica, and versicolor. In this blog, we will be discussing how to classify the …

Beginner’s Project on Regression in Python

Beginner’s Project on Regression in Python Machine learning regression is a type of machine learning where the goal is to predict a continuous value, such as a price or an age, based on a set of input features. It is used to model the relationship between a dependent variable and one or more independent variables. …

Beginner’s Project on Binary Classification in Python – Sonar Dataset

Beginner’s Project on Binary Classification in Python – Sonar Dataset Binary Classification is a type of machine learning problem where the goal is to classify instances into one of two classes. The Sonar Dataset is a popular dataset for binary classification problems, which is used to distinguish between metal cylinders and rocks from a sonar …

Beginner’s Project on Multi-Class Classification in Python

Beginner’s Project on Multi-Class Classification in Python Multi-class classification is a type of machine learning problem where the goal is to classify instances into one of multiple classes. This is different from binary classification, where the goal is to classify instances into one of two classes. There are several algorithms that can be used for …

How to save and load model with pickle

How to save and load model with pickle Saving and loading a model with pickle in Python is a way to preserve the trained model for future use. It allows you to save the model’s parameters, so you can use it later without the need to train the model again. This can save a lot …

How to save and load model with joblib

How to save and load model with joblib Saving and loading a model with joblib in Python is a way to preserve the trained model for future use. It allows you to save the model’s parameters, so you can use it later without the need to train the model again. This can save a lot …

How to do Random Search Cross Validation

How to do Random Search Cross Validation Random Search Cross Validation is a technique in machine learning that is used to find the best hyperparameters for a model, similar to Grid Search Cross Validation. Hyperparameters are the parameters of a model that are not learned from the data, such as the learning rate, the number …

How to do Grid Search Cross Validation in Python

How to do Grid Search Cross Validation in Python Grid Search Cross Validation is a technique in machine learning that is used to find the best hyperparameters for a model. Hyperparameters are the parameters of a model that are not learned from the data, such as the learning rate, the number of trees in a …

Applied Machine Learning with Ensembles: Voting Ensembles

Applied Machine Learning with Ensembles: Voting Ensembles Voting Ensemble is a machine learning algorithm in Python that combines multiple models to create a strong model. It is a type of ensemble method, which is a technique that combines the predictions of multiple models to improve the performance. The Voting Ensemble algorithm starts by training multiple …

Applied Machine Learning with Ensembles: Random Forest Ensembles

Applied Machine Learning with Ensembles: Random Forest Ensembles Random Forest Ensemble is a machine learning algorithm in Python that combines multiple decision tree models to create a strong model. It is a type of ensemble method, which is a technique that combines the predictions of multiple models to improve the performance. The Random Forest algorithm …