Data aggregation is a process in which data is gathered and represented in a summary form, for purposes including statistical analysis. It is a kind of information and data mining procedure where data is searched, gathered, and presented in a report-based, summarized format to achieve specific business objectives or processes ... Read More

Backpropagation defines the whole process encompassing both the calculation of the gradient and its need in the stochastic gradient descent. Technically, backpropagation is used to calculate the gradient of the error of the network concerning the network’s modifiable weights.The characteristics of Backpropagation are the iterative, recursive and effective approach through ... Read More

Feed-forward networkFeed-forward neural networks enable signals to travel one method only, from input to output. There is no feedback (loops) i.e., the output of any layer does not affect that same layer. Feed-forward networks influence to be easy networks that relate inputs with outputs. They are extensively used in pattern ... Read More

A neural network is a sequence of algorithms that endeavors to identify basic relationships in a set of data through a process that mimics the approach the human brain works. In this method, neural networks define systems of neurons, either organic or artificial.Neural Networks are analytic techniques modeled after the ... Read More

Association rule learning is a type of unsupervised learning technique that tests for the dependency of one data element on another data element and maps accordingly so that it can be more commercial. It tries to discover some interesting relations or associations between the variables of the dataset. It depends ... Read More

The approaches to mining multilevel association rules are based on the supportconfidence framework. The top-down strategy is employed where counts are accumulated for the calculation of frequent itemsets at each concept level, starting at concept level 1 and working towards the lower specific concept levels until more frequent itemsets can ... Read More

Web mining defines the process of using data mining techniques to extract beneficial patterns trends and data generally with the help of the web by dealing with it from web-based records and services, server logs, and hyperlinks. The main goal of web mining is to find the designs in web ... Read More

BaggingBagging is also known as bootstrap aggregation. It is the ensemble learning method that is generally used to reduce variance within a noisy dataset. In bagging, a random sample of data in a training set is selected with replacement meaning that the single data points can be selected more than ... Read More

There are various tools of data mining which are as follows −MonkeyLearn − MonkeyLearn is a machine learning platform that specializes in text mining. It is accessible in a user-friendly interface, so it can simply integrate MonkeyLearn with existing tools to implement data mining in real-time. It can begin immediately ... Read More

Data mining is the process of finding useful new correlations, patterns, and trends by transferring through a high amount of data saved in repositories, using pattern recognition technologies including statistical and mathematical techniques. It is the analysis of factual datasets to discover unsuspected relationships and to summarize the records in ... Read More