Author: Mathieu Carrière Translator: Sun Taochun Proofreader: He Zhonghua This article is approximately 4500 words long and is recommended to be read in 10minutes. This article briefly introduces the power of Topological Data Analysis (TDA) in machine learning and demonstrates how to practice with three Python libraries: Gudhi, Scikit-Learn, and Tensorflow. Tags: Data Visualization Hi … Read more
What is Scikit-learn? Scikit-learn is an open-source Python library that includes various unsupervised and supervised learning techniques. It is built on technologies and libraries such as Matplotlib, Pandas, and NumPy, which help simplify coding tasks. Features of Scikit-learn include: Classification (including K-Nearest Neighbors) Preprocessing (including Min-Max normalization) Clustering (including K-Means++ and K-Means) Regression (including Logistic … Read more
A simple technique for integrating decision trees involves training trees on subsamples of the training dataset. A subset of rows from the training data can be used to train individual trees known as bagging. When a subset of rows from the training data is also used when calculating each split point, this is referred to … Read more
Extreme Gradient Boosting (XGBoost) is an open-source library that provides an efficient implementation of the gradient boosting algorithm. Although other open-source implementations of this method existed before XGBoost, the release of XGBoost seems to have unleashed the power of the technique and brought gradient boosting to the attention of the machine learning community at large. … Read more
With the increasing popularity of Artificial Intelligence (AI) technology, various algorithms play a key role in driving the development of this field. From linear regression predicting housing prices to neural networks powering self-driving cars, these algorithms silently support the operation of countless applications. Today, we will give you a glimpse of these popular AI algorithms … Read more
With the increasing popularity of Artificial Intelligence (AI) technology, various algorithms play a key role in driving the development of this field. From linear regression for predicting housing prices to neural networks for self-driving cars, these algorithms silently support the operation of countless applications. Today, we will take you through these popular artificial intelligence algorithms … Read more
Click the "Advanced Programming" above and select the "Star" public account Super valuable content delivered to you immediately!!! In this article, we will demonstrate how to build a simple three-layer neural network from scratch. Although we will not derive all the mathematical operations involved in detail, I will do my best to explain our approach … Read more
KNN (K-Nearest Neighbors) algorithm is a simple yet effective classification and regression algorithm. Its basic idea is to classify or predict by calculating the distance between samples. Below is an example of KNN algorithm implementation in Python, including data preparation, model training, and prediction. 1. Install Required Libraries If you haven’t installed scikit-learn and numpy, … Read more
Full Article Link: https://tecdat.cn/?p=33917 KNN is a non-parametric learning algorithm, which means it makes no assumptions about the underlying data. This is a very useful feature because most client data does not really follow any theoretical assumptions, such as linear separability, uniform distribution, etc. (Click the “Read the Original” link at the end of the … Read more
Nearest Neighbor Algorithm Algorithm Principles The principle of the nearest neighbor method is to find a predefined number of training samples that are closest to the new point and predict the label from them. The number of samples can either be a user-defined constant (k-nearest neighbor learning) or can vary based on the local density … Read more