Categories: AI/ML Research

Tips for Effective Feature Selection in Machine Learning

When training a machine learning model, you may sometimes work with datasets with a large number of features. However, only a small subset of these features will actually be important for the model to make predictions. Which is why you need feature selection to identify these helpful features. This article covers useful tips for feature […]

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Tips for Effective Feature Engineering in Machine Learning

Feature engineering is an important step in the machine learning pipeline. It is the process of transforming data in its native format into meaningful features to help the machine learning model learn better from the data. If done right, feature engineering can significantly enhance the performance of machine learning algorithms.…

July 6, 2024

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Tips for Handling Imbalanced Data in Machine Learning

Introduction Imperfect data is the norm rather than the exception in machine learning. Comparably common is the binary class imbalance when the classes in a trained data remains majority/minority class, or is moderately skewed. Imbalanced data can undermine a machine learning model by producing model selection biases. Therefore in the…

May 25, 2024

In "AI/ML Research"

10 Python One-Liners for Feature Selection Like a Pro

In many data analysis processes, including machine learning , data preprocessing is an important stage before further analysis or model training and evaluation.

May 22, 2025

In "AI/ML Research"

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