Classifier

On Beloved TV Shows and Why Dimensionality of Data Matters I love Penguins of Madagascar, especially the TV series. Although the show was intended for kids, it portrays colorful personalities with prominent characteristics and contains many anecdotal moments for the grown up audience as well. In one of the episodes…

On Beloved TV Shows and Why Dimensionality of Data Matters I remember watching the original Cosmos series hosted by Carl Sagan on TV. I was only in elementary school and was not able to realize all the concepts but one of the key moments that remained with me until this…

Gradient Boosting Classifier is an ensemble machine learning algorithm that can be used for both classification and regression problems. It is a type of boosting algorithm, which means that it combines multiple weak models to form a single strong model. The main idea behind gradient boosting is to train a…

Hey Guys! I’m back in the saddle as a data sciencist trying out new things. …

“Multiple Classifier Systems”, or MCS, are Ensemble classifiers that combine some individual classifiers. This is a great new method for image classification, in particular for remote sensing images, that are images acquired by various sensors, as explained in the paper by P. Du at al. The main idea behind MCS…

My take on building a classifier in a sparse dataset — The subtitle may a bit misleading, I will admit that immediately. Not that I am not going to show you how to build a classifier that aims to predict the number of piglets born to a sow. No, what I mean is that the dataset is actually not that sparse…

CLASSIFY after you get CLARIFIED about the data 🚀 The major chunk of problem-solving with machine learning involves understanding how machine learning decisions are made when classifying. (Justifying the predictions that are made 🧠) Classification has diverse applications. One of the most predominant ones in the conversational AI landscape is…

This story is about decision trees, one of the most promising and popular non-parametric supervised machine learning technique. Decision trees are a hierarchical model of decisions and consequences. They are rooted trees with the root node having no incoming edges. …