Month: February 2019

How to implement Voting Ensembles in Python

How to implement Voting Ensembles in Python Voting Ensemble is a technique in machine learning where multiple models are combined to make a final prediction. The idea behind this technique is to leverage the strengths of different models to improve the overall accuracy of the final prediction. In this blog post, we’ll take a look …

How to compare SKLEARN classification models in Python

How to compare SKLEARN classification models in Python Comparing different machine learning models is an important step in the process of building a classifier. It allows you to evaluate the performance of different models and select the one that works best for your specific problem. In this blog post, we’ll take a look at how …

How to use Regression Metrics in Python

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 …

How to use Classification Metrics in Python

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

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

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 …

How to classify “wine” using SKLEARN Boosting Ensemble models – Multiclass Classification in Python

How to classify “wine” using SKLEARN Boosting Ensemble models – Multiclass Classification in Python In machine learning, one of the most common tasks is to classify data into different categories. For example, classifying different types of wine as red or white. In this blog post, we’ll take a look at how we can use a …

How to classify “wine” using SKLEARN Bagging Ensemble models – Multiclass Classification in Python

How to classify “wine” using SKLEARN Bagging Ensemble models – Multiclass Classification in Python In machine learning, the task of classifying wine is known as multiclass classification, as there are multiple classes (or types) of wine that need to be identified. One popular approach to improve the performance of a classifier is to use ensemble …

How to classify “wine” using SKLEARN Decision Tree models – Multiclass Classification in Python

How to classify “wine” using SKLEARN Decision Tree models – Multiclass Classification in Python In machine learning, the task of classifying wine is known as multiclass classification, as there are multiple classes (or types) of wine that need to be identified. One popular approach to multiclass classification is to use Decision Tree models. A Decision …

How to classify “wine” using SKLEARN LDA and QDA models – Multiclass Classification in Python

How to classify “wine” using SKLEARN LDA and QDA models – Multiclass Classification in Python In machine learning, the task of classifying wine is known as multiclass classification, as there are multiple classes (or types) of wine that need to be identified. One popular approach to multiclass classification is to use Linear Discriminant Analysis (LDA) …