Data Science

Data science is a category that covers a wide range of topics related to the analysis and interpretation of data. This category may include keywords such as data mining, machine learning, artificial intelligence, statistical analysis, data visualization, big data, predictive modeling, and data engineering.

In this category, you can find articles, resources, and insights related to data science, including best practices, tools, and techniques used by data scientists. Whether you are a beginner or an experienced practitioner, this category can help you stay up-to-date with the latest trends and techniques in data science. You can also find tutorials, case studies, and examples of real-world applications of data science in various fields, such as healthcare, finance, marketing, and more.

Deal with class imbalance (without generating synthetic samples): Clustering Based Bagging Algorithm (CBBA)

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to deal with class imbalance

To deal with class imbalance, take a look at “In classification, how do you handle an unbalanced training set?”. Definitely, the answers were very creative. The rookie way to deal with class imbalance The rookie’s way: The approach of under-sampling the majority class is an effective method in dealing with classifying imbalanced data sets. But … Read more

Understanding Heteroskedasticity and Transformations in Linear Regression Analysis

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Linear regression is a widely used statistical method for predicting outcomes based on input variables. However, analyzing the results of a linear regression model can be complicated, particularly when there is heteroskedasticity or a violation of the assumption of homoscedasticity. This can lead to incorrect or unreliable predictions and can be challenging to diagnose and … Read more

Curse of Dimensionality: An intuitive and practical explanation with examples

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“Curse of Dimensionality: An Intuitive and practical explanation with Examples”, this article will definitely consolidate your concept. “As the number of features or dimensions grows, the amount of data we need to generalize accurately grows exponentially.” Charles Isbell, Professor and Senior Associate Dean, School of Interactive Computing, Georgia Tech Curse of dimensionality The common theme … Read more

Exploring Model Performance Measures for Logistic Regression: Concordance Ratio, Somers’ D, and Kendall’s Tau

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As someone who is interested in logistic regression, you are likely familiar with the importance of measuring model performance. After all, accurately assessing the performance of a logistic regression model is crucial for making informed decisions based on the model’s predictions. In this blog post, we will explore three important measures of model performance for … Read more

Machine learning landscape 102: Unsupervised Learning, Semi-Supervised Learning & Unsupervised Learning

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Machine learning landscape 102

This post, “Machine Learning Landscape 102”, will answer the following questions: The last post, “Machine Learning Landscape 101“, tried to answer the following questions: Together, these two posts offer a solid foundation for anyone looking to gain a deeper understanding of machine learning and its various applications. Unsupervised Machine Learning Unsupervised learning is a type … Read more