Data Mining - (Descriptive|Discovery) (Analysis|Statistics)

Data System Architecture


Descriptive analysis is also known as Descriptive statistics

They are procedures used to summarize, organize, and simplify data.

Descriptive function are always unsupervised

See also Data Quality - Data Profiling.

By presenting information visually and allowing dynamic user control through direct manipulation principles, it is possible to traverse large information spaces and facilitate comprehension. In a few tenths of a second, humans can recognize features in megapixel displays, recall related images, and identify anomalies.

Type of identification

Division (Cluster)

Data Mining - Clustering (Function|Model)


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Data System Architecture
Data (Analysis|Analyse|Analytics)

finding the right data to answer abusiness question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have...
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Data Mining - (Feature|Attribute) Extraction Function

Feature extraction is the second class of methods for dimension reduction. dimension reduction It creates new attributes (features) using linear combinations of the (original|existing) attributes. ...
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Data Mining - (Function|Model)

The model is the function, equation, algorithm that predicts an outcome value from one of several predictors. During the training process, the models are build. A model uses a logic and one of several...
Data Mining - Clustering (Function|Model)

To identify natural groupings in the data. Useful for exploring data and finding natural groupings within the data. Members of a cluster are more like each other than they are like members of a different...
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Data Mining - Data Mining - (Data|Knowledge) Discovery - Statistical Learning

Data Mining can be defined as the automatic or semiautomatic task of extracting previously unknown information from a large quantity of data. Data mining try to discover in data unknown: unexpected...
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Machine Learning - Unsupervised Learning ( Mining )

Unsupervised learning is the second type of function that an algorithm can perform. The algorithm is said to be unsupervised when no response is used in the algorithm. Unsupervised Learning has the goal...
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is a scientific discipline devoted to the study of data. is the art of extracting information from data. From Data to Information to Knowledge. No learning. lies lies, damned lies, and statistics....
Data System Architecture
Statistics - (Data|Data Set) (Summary|Description) - Descriptive Statistics

Summary are a single value summarizing a array of data. They are: selected or calculated through reduction operations. They are an important element of descriptive analysis One of the most important...
Overfitting Underfitting
Statistics - (Variance|Dispersion|Mean Square) (MS)

The variance shows how widespread the individuals are from the average. The variance is how much that the estimate varies around its average. It's a measure of consistency. A very large variance means...
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Statistics - Characteristic, Property, Nature

Characteristic, Property, Nature are used to describe. Characteristic, Property and/or Nature of a data set can be described through: statistic and parameters Characteristic, Property and/or...

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