Chapter 3- predictive models

What is the 2 types of variables in Linear Regression?

• Invisible and visible variable.

• dependent variable and independent variable.

• transparent variable

• independent and visible variable.

What is the statistical model?

• Predictive Paradigm.

• Machine learning.

• statistical learning.

• Mathematical representation of observed data.

What are 4 types of data analysis?

• 1) Structured data

  2) Unstructured data

  3) Semi-structured data

  4)

• 1) Linear regression

  2) KNN

  3) Decision Tree

  4) Neural Network

• 1) Data Profiling

  2) Data cleansing

  3) Data transformation

  4)Data validation

• 1) Descriptive

  2) Diagnostic

  3) Predictive

  4) Prescriptive

Simple Linear Regression is one of linear regression. choose the the other type of linear regression.

• Multiple linear regression

• One layer regression

• Duplex regression

• non-linear regression

What is KNN?

• Clustering algorithm is used to find groups which have not been explicitly labeled in the data

• Simplest forms of machine learning algorithms mostly used for classification. It classifies the data point on how its neighbor is classified

• Used in applications like handwriting recognition, intrusion detection, face detection, email classification, gene classification, and in web pages.

The advantages of decision tree (DT)

• 1) Interpretability. 2) Less Data Preparation.

  3) Non-Parametric. 4) Versatility.

• 1) Overfitting

  2) Feature Reduction & Data 3) Resampling.

  4) Optimization.

• unstable

Model of neuron consists of?

• 1) Nucleus

  2) cell

  3) Neutron

• 1) Dendrites

  2) synapse

  3) soma

  4) Axon

• 1) Axon

  2) Myelin Sheath

  3) Node

  4) Cell of body

List 2 types of architecture of NN.

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What is SVM?

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What are the differences between classification and clustering?

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