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What is the difference between Descriptive and Predictive Data Mining?
Descriptive Data Mining
Descriptive mining is generally used to provide correlation, cross-tabulation, frequency, etc. These methods are used to decide the data's regularities and to reveal patterns. It focuses on the summarization and conversion of records into significant data for reporting and monitoring.
Descriptive mining "describes" the data. Once the data is captured, it can modify it into human interpretable form. In descriptive data mining, an association technique that uses Apriori algorithms to characterize student performance to find co-relations between a set of items.
The Apriori algorithm is used in the database including academic records of several students and tries to extract association rules to profile students based on several parameters such as exam scores, term work grades, attendance, and practical.
Predictive Data Mining
The term 'Predictive' defines to predict something, so predictive data mining is the analysis done to predict the future event or multiple data or trends. Predictive data mining can allow business analysts to create decisions and insert a value into the analytics team efforts. Predictive data mining provides predictive analytics. In predictive analytics, it is the use of data to predict outcomes.
The main goal of predictive mining is to predict future results rather than current behavior. It includes the supervised learning services used for the prediction of the focus value.
The approaches that fall under this mining element are classification, time-sequence analysis, and regression. Data modeling is the fundamental of predictive analysis, which works by using some variables to anticipate the unknown future data values for other variables.
Additionally, it also conducts the comparison between these supervised learning methods for obtaining the prescience about the strength and weaknesses of each method. This entire process is implemented to discover out the most suitable techniques for extracting the desired knowledge.
Let us see the comparison between Descriptive Data Mining and Predictive Data Mining.
| Descriptive Data Mining | Predictive Data Mining |
|---|---|
| Descriptive mining is generally used to support correlation, cross-tabulation, frequency, etc. | The term 'Predictive' defines to predict something, so predictive data mining is the analysis done to predict the future event or multiple data or trends. |
| It defines the features of the data in a target data set. | It executes the induction over the current and past records so that predictions can appear. |
| It requires data aggregation and data mining. | It requires statistics and data forecasting procedures. |
| The descriptive analysis only responds to the situation. | The predictive analysis includes control over the situation along with responding to it. |
| It can support accurate records. | It makes results does not provide accuracy. |
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