Tag Archives: model validation

How to setup a Deep Learning Model in Keras

Hits: 206    Deep learning is a type of machine learning that uses neural networks with multiple layers, called deep neural networks, to analyze and understand complex data, such as images, speech, and text. In this essay, we will be discussing how to set up a deep learning model using Keras, a popular open-source library …

SKLEARN Gradient Boosting Classifier with Monte Carlo Cross Validation

Hits: 122SKLEARN Gradient Boosting Classifier with Monte Carlo Cross Validation   Gradient Boosting Classifier is a machine learning technique used to classify items into different categories. It is an ensemble method that combines the predictions of multiple weak models, such as decision trees, to make a final prediction. The technique uses an iterative process where …

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

Hits: 85IRIS 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 …

Evaluate Machine Learning Algorithm – repeated kfold cross validation in R

Hits: 48 Evaluate Machine Learning Algorithm – repeated kfold cross validation in R Evaluating the performance of a machine learning algorithm is an important step in understanding how well it will work on new, unseen data. One popular method for evaluating the performance of an algorithm is called “repeated k-fold cross validation.” In repeated k-fold …

How to setup a Machine Learning Classification problem in R

Hits: 159How to setup a Machine Learning Classification problem in R Setting up a machine learning classification problem in R involves several steps, such as loading the data, preparing the data, selecting and training a model, and evaluating the model’s performance. Loading the data: The first step is to load the data into R, which …

How to classify “wine” using SKLEARN linear_models – Multiclass Classification in Python

Hits: 1196How to classify “wine” using SKLEARN linear_models – Multiclass Classification in Python Classifying wine can be an important task for those in the wine industry. In machine learning, this task is known as multiclass classification, as there are multiple classes of wine that need to be identified. One popular approach to multiclass classification is …

How to use SVM Classifier and Regressor in Python

Hits: 147How to use SVM Classifier and Regressor in Python Support Vector Machine (SVM) can be used for both Classification and Regression tasks. In classification, the goal is to assign a label to a given input, like determining which digit the image represents (0-9) from an image of a handwritten digit. In Regression, the goal …

How to use GradientBoosting Classifier and Regressor in Python

Hits: 118How to use GradientBoosting Classifier and Regressor in Python Gradient Boosting is a powerful ensemble machine learning algorithm that creates multiple decision trees and combines their predictions to make more accurate predictions. It is used for both classification and regression problems. In this article, we will go over the basics of how to use …

How to use RandomForest Classifier and Regressor in Python

Hits: 121How to use RandomForest Classifier and Regressor in Python Random Forest is an ensemble machine learning algorithm that creates multiple decision trees and combines their predictions to make more accurate predictions. It is used for both classification and regression problems. In this article, we will go over the basics of how to use Random …

How to use AdaBoost Classifier and Regressor in Python

Hits: 466How to use AdaBoost Classifier and Regressor in Python AdaBoost is an ensemble machine learning algorithm that combines several weak models to create a strong model. It is used for both classification and regression problems, and it’s commonly used with decision tree models. In this article, we will go over the basics of how …

How to create and optimise a baseline Linear Regression Model in Python

Hits: 191How to create and optimise a baseline Linear Regression Model in Python Linear Regression is a popular method of statistical analysis that can be used to predict a continuous variable based on a set of input variables. In this article, we will go over the basics of how to create and optimize a linear …

How to optimise hyper-parameters of a DecisionTree Model using GridSearchCV in Python

Hits: 39How to optimise hyper-parameters of a DecisionTree Model using GridSearchCV in Python When building a machine learning model, it’s important to optimize the parameters of the model for the best performance. One way to do this is by tuning the hyper-parameters of a DecisionTree model using GridSearchCV. A Decision Tree model is a simple …