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What Is Data Mining & The Process Of Data Mining?

Introduction to Data Mining Methods

The usage of Data is increasing on a day-to-day basis at an enormous scale. However, all the data which is collected from multiple sources isn’t useful for the business as there will be the presence of garbage data. So, before beginning with the process of analyzing the data it is the responsibility of a Data Scientist to separate meaningful data from noisy data (meaningless data). This process of separation is done by a technique called Data Mining.

In this blog post let’s know what exactly is the process of Data Mining?

What is Data Mining?

Data Mining can be interpreted as the process of extracting insights from the enormous levels of data which is referred to as big data. This process is successfully carried out by making use of different data mining tools. Data mining can also be referred as Knowledge discovery from data or KDD.

Different Data Mining Methods-

Dining Mining is a crucial step in the data exploratory process. At present, there are several techniques that help in the process of Data Mining. Some Data Mining Methods are:

  • Association
  • Classification
  • Clustering Analysis
  • Prediction
  • Sequential Patterns or Pattern Tracking
  • Decision Trees
  • Outlier Analysis or Anomaly Analysis
  • Neural Network

Classification-

By making use of Classification it becomes easy in distinguishing the items in the data sets into classes or groups. Also, this process helps in accurately predicting the behavior of items within the group. It is a two step process:=

  • Learning Step: In this, a classification algorithm builds the classifier by analyzing a training set.
  • Classification Step: Test data are used to estimate the accuracy or precision of the classification rules.

Clustering Analysis-

The process of Clustering is quite similar to classification & here clusters are made depending on the similarities of data items. The process of Clustering is also called as data segmentation as it partitions huge data sets into clusters according to the similarities.

There are various clustering methods that are used:

  • Hierarchical Agglomerative methods
  • Grid-Based Methods
  • Partitioning Methods
  • Model-Based Methods
  • Density-Based Methods

Neural Network-

This process of Data Mining is quite similar to that of the biological neural networks in the human brain. Neural Networks are the collection of neurons like processing units with weighted connections between them. It is used for classification, regression analysis, data processing etc. This technique works on three pillars

  • Model
  • Learning Algorithm (supervised or unsupervised)
  • Activation function

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