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Metrics of classification

While solving classification problem, there are certain metrics that are to be studied before making any decision. Some of the metrics include confusion, matrix, ROC curve, etc. Let’s study these matrices by practical use case. For this demonstration, I choose the breast cancer dataset provided by sklearn. Let’s first split the data set in to…

Boosting

Boosting is the most common type of classes of algorithm performed globally to solve various kind of problems. It comprises of several weak learners or machine learning models which work together to compromise for the unlearnt pattern or miss-classified data points by the preceding model, through prioritizing those data points. One of the most commonly,…

Sigmoid function and its applications

Starting with very basics, let’s understand what is sigmoid? Sigmoid is just a mathematical function given by the following expression: When plotted, it forms a ‘S’ like curve ranging between 0 and 1: In the realm of machine learning, we can use this function for our advantage. It can be used for classification problems where…

PCA

PCA stands for Principal Component Analysis. To explain in simple words, it is a process of dimensional reduction of data without loosing any significant information. We will be looking towards the entire algorithm and understand step by step. Let’s first build an arbitrary data set and plot it to have a visual representation of the…

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About Me

Hi, I’m Tuhin. Previously a quality engineer, I became a full-time data scientist and blog writer in 2021. I spend most of my time working with ML and data science projects which is indeed my passion. These blogs are for explaining some topics hoping to make things clearer for others.

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