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Is least squares regression the same as linear regression
Last Updated: 12 November 2024
Yes, Least squares regression and linear regression are closely related in machine learning, but they’re not quite the same. Linear regression is a type of predictive mode...
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Can Linear Regression be used with Binary Independent Variables?
Last Updated: 25 November 2024
Yes, linear regression can work with binary independent variables, where the variable only takes two values, such as 0 and 1. These binary predictors are used to distingui...
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When to normalize data in regression?
Last Updated: 12 November 2024
Normalization, or scaling, is the process of adjusting the values of features to a common scale without distorting differences in the data. When working with regression mo...
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Does Linear Regression Require Feature Scaling?
Last Updated: 19 November 2024
Linear regression does not always require feature scaling, but scaling can improve its performance and help in specific cases. The main reason is that linear regression mo...
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How to choose ideal Decision Tree depth without overfitting?
Last Updated: 09 January 2025
Choosing the ideal depth for a decision tree is crucial to avoid overfitting, a common issue where the model fits the training data too well but fails to generalize to new...
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How to choose α in cost-complexity pruning?
Last Updated: 09 January 2025
Cost-complexity pruning is a method used in decision trees to balance the trade-off between accuracy and complexity, helping to prevent overfitting. The key parameter in t...
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How do decision trees work with unbalanced datasets?
Last Updated: 25 November 2024
Decision trees are a popular machine learning model for classification tasks. However, when dealing with unbalanced datasets—where one class significantly outnumbers the o...
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How to save a decision tree in ONNX format for deployment?
Last Updated: 25 November 2024
To save a decision tree in ONNX format for deployment, you can use the skl2onnx library, which converts scikit-learn models to the ONNX format. ONNX (Open Neural Network E...
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How do k-means clustering methods differ from k-nearest neighbor methods
Last Updated: 13 January 2025
K-Means is an unsupervised learningmethod used for clustering, while KNN is a supervised learning algorithm used for classification (or regression). K-Means clusters data...
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Why is KNN a lazy learner?
Last Updated: 12 November 2024
The K-Nearest Neighbors (KNN) algorithm is known as alazy learnerbecause it does not build an internal model during the training phase. Instead, it simply stores the entir...
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How to Visualize KNN in Python
Last Updated: 25 November 2024
Visualizing the K-Nearest Neighbors (KNN) algorithm in Python is a great way to understand how this supervised learning method works and how it makes predictions. In essen...
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How to choose the right distance metric in KNN?
Last Updated: 15 January 2025
Choosing the right distance metric is crucial for K-Nearest Neighbors (KNN) algorithm used for classification and regression tasks. Distance metric determines how the algo...
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Training a decision tree against unbalanced data
Last Updated: 21 April 2025
When building machine learning models like decision trees, imbalanced data—where one class significantly outnumbers another—presents a unique challenge. For example, in cr...
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What is the influence of C in SVMs with linear kernel?
Last Updated: 25 November 2024
Support Vector Machines (SVMs) are powerful machine learning algorithms used for classification and regression tasks. When dealing with linearly separable data, SVMs use a...
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Instance Normalization vs Batch Normalization
Last Updated: 15 January 2025
Instance normalization and batch normalization are techniques used to make machine learning models train better by normalizing data, but they work differently. Instance no...
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