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Integration of Techniques
k-Fold cross-validation Read more on this free link
K-means Clustering for Customer Segmentations: A Practical Real-world Example Read more on this free link
Machine Learning Basics with the K-Nearest Neighbors Algorithm Read more on this free link
CART (Classification and Regression Trees) can be used for both classification and regression problems. The difference lies in the target variable. Meanwhile, regression is used to predict a numerical label Read more on this free link
k-Nearest Neighbors and Cross-validation Read more on this free link
Introduction to K-means Clustering. K-means clustering is a type of unsupervised learning, which is used when you have unlabeled data Read more on this free link
The decision tree Algorithm belongs to the family of supervised machine learning algorithms. It can be used for both a classification problem as well as for regression problem Read more on this free link
What Is Overfitting? Overfitting is a modeling error in statistics that occurs when a function is too closely aligned to a limited set of data points. As a result, the model is useful in reference only to its initial data set, and not to any other data sets Read more on this free link
The Statistics Of KNN Parameter Optimization. Read more on this free link
The above content addresses the K-nearest neighbor along with the python code. The content also states the application of Machine Learning in sectors such as Health Care, Sports, Banking, etc. Read more on this free link
Introduction to k-Nearest Neighbors: A powerful Machine Learning Algorithm (with implementation in Python & R). Read more on this free link
How to deal with Cross-Validation based on KNN algorithm Read more on this free link
K-means clustering is a very popular unsupervised learning algorithm. In this article I want to provide a bit of background about Read more on this free link
Application of regression analysis Read more on this free link
A Practical Application of K-Nearest Neighbours Analysis Read more on this free link
- Decision Trees for Classification: A Machine Learning Algorithm
- Decision Tree Classification Algorithm
- Decision Trees in Machine Learning
- Development and applications of Decision Trees
- Decision tree methods: applications for classification and prediction
- Decision Tree Algorithm Explained with Examples
- Six Powerful Use Cases for Machine Learning in Manufacturing
- Use cases of Different Machine Learning Algorithms
- When to Use Linear Regression, Clustering, or Decision Trees
Case studies using K-NN
- kNN approach to unbalanced data distributions: A case study involving information extraction
- Predicting the quality of the car
- Microarray gene expression analysis and clinical outcome prediction
- Credit Card Fraud Detection
- Credit card fraud detection in internet using kNN algorithm
- Predicting Cardiovascular Disease
- Heart Disease Prediction using KNN -The K-Nearest Neighbours Algorithm
- Classifying Heart Disease Using K-Nearest Neighbors
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