Categories:
This algorithm works by assigning membership to each data point corresponding to each cluster center on the basis of the distance between the cluster center and the data point. The more the data is near to the cluster […]
Categories:
k-means is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters. The main idea […]
Categories:
In Data mining C4.5 algorithm is used as a Decision Tree Classifier, which employed to generate decisions that are based on a certain sample of data. A decision tree nearly looks like any flow chart, which has some […]
Categories:
Clustering is the undertaking of separating the populace or information that focuses on various gatherings with the end goal that information focuses on similar gatherings are more like other information focuses on a similar gathering than those in […]
Categories:
A decision tree is a type of Supervised Learning. In which we continuously split data according to some fixed parameters. It has two entities which are decision nodes and leaves. Where leaves are the final outcome of the […]
Categories:
CART stands for Classification And Regression Trees. It is a widely used technology in machine learning. It is a predictive model that explains that the value of an outcome can be predicted which would be based on other […]
Categories:
ID3 is a decision tree algorithm. ID3 is an abbreviation for Iterative Dichotomiser 3. It was invented by J. Ross Quinlan in 1975. It uses a fixed set of examples to build a decision tree. The resulting tree […]
Categories:
AES algorithm is a symmetrical block cipher algorithm that takes in input the plain text in blocks of 128 bits and converts them using keys of 128, 192, and 256 bits in the Ciphertext. It is used by […]