rbf-kernel

cat🐈: the repo for the paper "Embarrassingly Simple Unsupervised Aspect extraction"

C++ Implementation of the RBF (Radial Basis Function) Network and choosing centroids using K-Means++

ProtVec can be used in protein interaction predictions, structure prediction, and protein data visualization.

I apply machine learning (ML) techniques to Snowplow web event data to understand how variation in marketing site experiences might correlate to customer conversion.

Image Processing and classification using Machine Learning : Image Classification using Open CV and SVM machine learning model

To deal with non-linearly separable we use SVM's Kernel Trick which maps data to higher dimension!

Breast Cancer Coimbra Data-set

Access the Linear or RBF kernel SVM from OCaml using the R e1071 or svmpath packages

SPPU - BE ENTC (2015 Pattern) - Elective III

Numpy based implementation of kernel based SVM

MATLAB implementations of different learning methods for Radial Basis Functions (RBF)

In This Notebook I've build a Machine-Learning model that normalize region names in Damascus city, then I use it in Locator class.

GISETTE is a handwritten digit recognition problem. The problem is to separate the highly confusible digits ‘4’ and ‘9’. This dataset is one of five datasets of the NIPS 2003 feature selection challenge.

PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM

💚 A heart disease classifier using 4 SVM kernels and decision trees, with PCA, ROC, pruning, grid search cv, confusion matrix, and more

Multiclass Multilabel Classification using SVM on Frogs Dataset

Generalized Improved Second Order RBF Neural Network with Center Selection using OLS

kernalized t-Distributed Stochastic Neighbor Embedding (t-SNE)

This code reads a dataset i.e, "Heart.csv". Preprocessing of dataset is done and we divide the dataset into training and testing datasets. Linear, rbf and Polynomial kernel SVC are applied and accuracy scores are calculated on the test data. Also, a graph is plotted to show change of accuracy with change in "C" value.

Classifying purchase events with introduction of dimensions to linearly separate the data points. The SVM algorithm uses Radial basis Function (RBF) Kernel.