Data Mining

Bagging and Boosting

Ensemble Learning approach in Data Mining

In our day to day life, when crucial decisions are made in a meeting, a voting among the members present in the meeting is conducted when the opinions of the members conflict with each other. This principle of “voting” can be applied to data mining also. In the voting scheme, when classifiers are combined, the class assigned to a test instance will be the one...

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Data Classification

Classification in Data Mining

Classification is the process of finding a model (or function) that describes and distinguishes data classes or concepts, for the purpose of being able to use the model to predict the class of objects whose class label is unknown. The derived model is based on the analysis of a set of training data (i.e., data objects whose class label is known). Classification predicts categorical (discrete,...

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KMeans Clustering with Example

KMeans Clustering With Example

Clustering is the process of making a group of abstract objects into classes of similar objects. Having similarity inside clusters to be high and low clustering similarities between the clusters. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the...

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PPDM Techniques

Privacy Preserving Data Mining (PPDM) Techniques

Based on the five dimensions explained in the previous blog different PPDM techniques can be categorized into following categories. PPDM is divided into two parts centralized and distributed which is further categorized into 5 techniques. 1. Anonymization Based: Anonymization is a technique in which record owner’s identity or sensitive data remain hidden. In a table, the most basic form of data consists of four types...

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Privacy Preserving Data Mining

Privacy Preserving Data Mining

Data mining is one of the rapidly increasing fields in the computer industry that deals with extracting patterns from large data sets. It is used to extract human understandable information. Moreover, data mining plays an important role in many business organizations, financial, educational and health companies and revealing sensitive information is a big harm. From the point of view of the organization, mining is helpful...

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PhD thesis Topics

Latest PhD topics in computer science

Latest Ph.D. thesis topics in computer science is all about what practical knowledge you have gained in your B.Tech, Selecting a decent dissertation topic is significant, as this can offer a powerful foundation upon that to make the remainder of the work. A weak treatise topic can inevitably result in a weak dissertation; one thing that you would like to avoid happening in the...

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Association rule mining

Association Rule Mining

Association rules are one of the major techniques of data mining. It finds frequent patterns, associations, correlations or informal structures among sets of items or objects in transactional databases and other information repositories.It is one of the most important data mining tasks, which aims at finding interesting associations and correlation relationships among large sets of data items. A typical example of association rule mining is...

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Sentiment Analysis Block diagram

Sentiment Analysis

Sentiment analysis can be termed as opinion mining. It uses Natural Language Processing (NLP), Computational fundamentals and text analysis to recognize and extract subjective information in source materials. It can also be termed as Review mining and Appraisal Extraction. Synonyms of Opinion The basic task of sentiment analysis is to classify the given text on the basis of polarity at the document level, sentence level...

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