Basics of Data Mining

_____ is when any data point deviate fully from rest of the data points in a dataset.

• Contextual outlier

• Collective outlier

• Point outlier

• Recent outlier

The random error or variance in data is called ____.

• noise

• outlier

• duplicate value

• missing value

_____ method identifies the relation among two dependent attributes so that if we have one attribute, it can be used to predict the other attribute.

• Regression

• Clustering

• Classification

• Normalization

summarize the data after integrating it collected from various sources is called as ______.

• Regression

• Normalization

• Aggregation

• Smoothing

_____ divides the continuous attributes values into intervals by top-down and bottom-up techniques

• Normalization

• Discretization

• Aggregation

• Regression

____ is an abstract concept that refers to that which has the power to inform.

• Pattern

• Data

• Information

• Knowledge

A ____ is a series of data that repeats in a recognizable way.

• Information

• Data

• Knowledge

• Pattern

The primary benefit of data mining is its power to ______.

• organized the data

• collection of data

• identify patterns and relationships

• normalized data

An ____ is a data field, representing a characteristic or feature of a data object.

• pattern

• attribute

• data

• object

Symbols or names (or numbers) of things is ____ type of attribute.

• Nominal

• Binary

• Ordinal

• Numeric