What is stratified bootstrap?
jacksparrow What is Stratified Bootstrap? What is Stratified Bootstrap? Stratified bootstrap is a resampling technique used in statistics to estimate the sampling distribution of a statistic. It is a variation of…
September 2024
Improving k-means clustering
Improving k-means clustering Improving k-means clustering K-means clustering is a popular and widely used algorithm for partitioning data into k clusters. While simple and efficient, it can suffer from certain…
Artificial Intelligence Methods to Detect Cheating in Games
Artificial Intelligence Methods to Detect Cheating in Games Artificial Intelligence Methods to Detect Cheating in Games The rise of online gaming has led to an increase in cheating, which can…
Need help designing fitness evaluation for a NEAT algorithm-based neural network
Designing Fitness Evaluation for a NEAT Algorithm-based Neural Network Need help designing fitness evaluation for a NEAT algorithm-based neural network Understanding NEAT and Fitness Evaluation The NeuroEvolution of Augmenting Topologies…
What are the differences between airflow and Kubeflow pipeline?
Airflow vs Kubeflow Pipelines Airflow vs Kubeflow Pipelines: A Comprehensive Comparison Both Airflow and Kubeflow Pipelines are powerful workflow orchestration tools designed to streamline complex data pipelines. While they share…
difference between LinearRegression and svm.SVR(kernel=”linear”)
Linear Regression vs. SVM with Linear Kernel Linear Regression vs. SVM with Linear Kernel Both Linear Regression and Support Vector Machines (SVM) with a linear kernel are supervised learning algorithms…
how to use weight when training a weak learner for adaboost
Using Weights in Adaboost for Weak Learners Boosting Weak Learners with Weights in AdaBoost AdaBoost (Adaptive Boosting) is a powerful ensemble learning method that combines multiple weak learners to create…
An understandable clusterization
An Understandable Clusterization What is Clusterization? Clusterization, also known as clustering, is a fundamental technique in unsupervised machine learning. Its purpose is to group similar data points together into clusters…
Example of implementation of Baum-Welch
Example of Implementation of Baum-Welch Algorithm Introduction The Baum-Welch algorithm is an iterative algorithm used to estimate the parameters of a Hidden Markov Model (HMM). This algorithm is used in…
Algorithm to classify a list of products? Take 2
Algorithm to Classify a List of Products Algorithm to Classify a List of Products Introduction Classifying products is a fundamental task in e-commerce, inventory management, and data analysis. This article…