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Category Archives: Data Mining

Data mining is also called discovering the knowledge in data, basically, it is the process of uncovering the various patterns and valuable information from given… Read More
Backpropagation is an algorithm that back propagates the errors from output nodes to the input nodes. Therefore, it is simply referred to as backward propagation… Read More
CLIQUE is a density-based and grid-based subspace clustering algorithm. So let’s first take a look at what is a grid and density-based clustering technique.  Grid-Based… Read More
STING is a Grid-Based Clustering Technique. In STING, the dataset is recursively divided in a hierarchical manner. After the dataset, each cell is divided into… Read More
The ANN(Artificial Neural Network) is based on BNN(Biological Neural Network) as its primary goal is to fully imitate the Human Brain and its functions. Similar… Read More
Dimension reduction is a necessary step in the effective analysis of massive high-dimensional datasets. It may be the main objective in Data Mining for the… Read More
Active learning is an iterative type of supervised learning and this learning method is usually preferred if the data is highly available, yet the class… Read More
Transfer learning is the way in which humans apply their knowledge in a task to learn another task. Transfer learning gains the knowledge from one… Read More
The Complex data types require advanced data mining techniques. Some of the  Complex data types are sequence Data which includes the Time-Series, Symbolic Sequences, and… Read More
A cluster is the collection of data objects which are similar to each other within the same group. The data objects of a  cluster are… Read More
GSP is a very important algorithm in data mining. It is used in sequence mining from large databases. Almost all sequence mining algorithms are basically… Read More
Clustering is basically a type of unsupervised learning method. An unsupervised learning method is a method in which we draw references from datasets consisting of… Read More
A database may contain data objects that do not comply with the general behavior or model of the data. These data objects are Outliers. The… Read More
To find a numerical output, prediction is used. The training dataset contains the inputs and numerical output values. According to the training dataset, the algorithm… Read More
A data mining technique that is used to uncover purchase patterns in any retail setting is known as Market Basket Analysis. In simple terms Basically,… Read More

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