… is a c-means hybrid model and the second one is k-means, to feed … been used to predict
heart disease, using a database with … of heart disease using artificial neural network and feature …

… for weather forecasting with K-Means. Kurniawan and Fatulloh [37] used the K-Means algorithm
… By optimizing the coefficients, we aimed to address the issue of the K-Means approach …

… The flatten neuron of the feature map for every image resulted … k-means clustering algorithm.
This algorithm then used to obtain the centroid of each cluster that determines the prediction …

… , Support Vector Machine, k- means clustering. This paper … methods: Decision Tree, Naive
Bayes, and Neural Network … developed based on the Hybrid approaches which merge the …

… diseases are incurable, such as cancer, stroke, heart attack, … hybrid approach, the labeled
features of both k-means and … include artificial intelligence, artificial neural networks, deep …

… Multi-Layer Perceptron Neural network (MLP) with back … Naïve Bayesian classifier and
K-means algorithms. Their … a hybrid approach for heart disease prediction using machine learning …

… Prediction of heart disease at early stage using data mining and big data analytics: A survey.…
Smart heart disease prediction system using Improved K-means and ID3 on big data." Data …

… prediction technique based on convolutional neural networks… The performance of the K-means
algorithm in terms of … of proposed Heart Disease Predictions is evaluated using …

… The hybrid method can be defined as an algorithm type that can … the learning process of
artificial neural networks. The weight … [14] Çalışkan, SK, & Soğukpınar, İ., “KxKNN: K-means ve k …