SHStat Hacksinadvanced-data-professionals.hashnode.dev·Jun 16 · 9 min readLevel 2 Predictors in Multi Level ModellingNote: this post is part of a series of posts regarding my comprehensive guide to Multi Level Modelling What are Level 2 Predictors? As the name implies - these factors vary at Level 2 - instead of Lev00
ACAnik Chandinanikchandml.hashnode.dev·May 23 · 4 min read#8 Linear RegressionLinear Regression is a supervised machine learning algorithm used for predicting continuous numerical values. It finds the relationship between input variables and output variables using a straight li00
MMacaulay001inforgottentheorieshashnodedev.hashnode.dev·May 11 · 6 min readI refit Galton's 1886 height data. The slope is still 0.66, not 1.Part 88 of Forgotten Theories, a series re-testing old scientific claims with modern tools. Find the rest under the #forgotten-theories tag. Francis Galton spent a chunk of the 1880s measuring families. He had his Anthropometric Laboratory at South ...00
DKDivyajot Kaurinai-beginners-journey.hashnode.dev·Apr 30 · 4 min readPart 4: Regression vs Classification: How Machines Predict & DecideIn the previous blog, we explored what Supervised Learning is and how models learn from data. Now, let's understand how Supervised Learning is used to solve real-world problems using two key approache00
PPPranoti Patilinai-for-multidisciplinary-application.hashnode.dev·Mar 6 · 3 min read21.1 Introduction of Decision TreesHave you ever noticed that your life already runs on a decision tree? If it’s raining → take an umbrella Else if it’s sunny → take sunglasses Else → just pray and go out Congratulations! You just00
PPPranoti Patilinai-for-multidisciplinary-application.hashnode.dev·Mar 6 · 4 min read22.3 Illustration of K-Means Clustering Using a Sample Dataset To understand how the K-Means clustering algorithm works, let us consider a small customer dataset.Each customer is represented using two attributes: Annual Income and Spending Score.The objective of 00
PPPranoti Patilinai-for-multidisciplinary-application.hashnode.dev·Mar 6 · 3 min read21.3 Numerical example of decision tree using ID3Numerical example of decision tree using ID3Suppose, we have, 2 featuresFeature 1,(Feature = F1)Feature ExplanationRoot Node:Feature → 9 Yes / 5 No First Split (C1):6 Yes / 2 No → More pure node00
PPPranoti Patilinai-for-multidisciplinary-application.hashnode.dev·Mar 6 · 3 min read22.2 How to Apply K-Means Clustering Algorithm Suppose we have 8 data points on a graph.Our goal is to group these points into clusters using the K-Means algorithm. Step 1: Choose the Number of Clusters (K) First, we decide how many clusters we00
PPPranoti Patilinai-for-multidisciplinary-application.hashnode.dev·Mar 6 · 5 min read22. K-Means ClusteringIntroduction to Cluster Have you ever noticed that customers in a mall don’t behave the same?”Some people earn high salary but spend less,some earn less but spend more,and some are in between. Can we 10
PPPranoti Patilinai-for-multidisciplinary-application.hashnode.dev·Mar 6 · 4 min read21.2 ID3 (Iterative Dichotomiser 3)ID3 (Iterative Dichotomiser 3) is a popular algorithm used to construct a decision tree for classification problems. It selects the best attribute for splitting the data based on Information Gain, whi00
