## Precision-Recall Curve for Classification model analysis

Accuracy is something which gives an intuition of model performance. i.e. ratio of number of correct predictions with respect to total sample present. But what in case of unbalanced data.Imagine a case where we need to make a model to predict click through rate over a display rate. The click trough rate used to be […]

## The ROC – AUC curves for Classification based Model Performance Analysis

Accuracy is something which gives an intuition of model performance. i.e. ratio of number of correct predictions with respect to total sample present. But what in case of unbalanced data.Imagine a case where we need to make a model to predict click through rate over a display rate. The click trough rate used to be […]

## Decision Tree Algorithm and Gini Index using Python

Decision Tree Classification Algorithm is used for classification based machine learning problems. It is one of the most popular algorithm as the final decision tree is quite easy to interpret and explain. More advanced ensemble methods like random forest, bagging and gradient boosting are having roots in decision tree algorithm. Here we will try to […]

## KNN Algorithm and Maths behind

KNN or K – Nearest Neighbours is one the powerful algorithm used in classification based problems to successfully make categorical predictions. Scikit-Learn gives us built in library to use and make the process easier for us if we are having data. But here we will write KNN code mathematically without any inbuilt library to figure […]

## Mean, Variance, Standard Deviation, Standard Score, Covariance & Data Projection

Variance – It is the measure of squared difference from the Mean. To calculate it we follow certain steps mentioned below: Calculate average of numbers For each numbers subtract the mean and square the result Calculate the average of those squared differences i.e. Variance Editorial Team