Hi folks,
I'm sharing this generic and practical approach that can be applied to most of the machine learning algorithms...
Don't get confuse!!!
Road map towards the understanding of WHICH Algorithm to use WHEN
First of all need to understand, The Nature of Data:
There are major two types of data:
1. Quantitative: i.e Numeric (comprises of Integer, Continuous)
2. Qualitative i.e Categorical
This Categorical further divided into 2 types: 1. Nominal 2. Ordinal
According to the nature of data, algorithm is chosen:
Hope! This is useful to you.
I'm sharing this generic and practical approach that can be applied to most of the machine learning algorithms...
Don't get confuse!!!
Road map towards the understanding of WHICH Algorithm to use WHEN
First of all need to understand, The Nature of Data:
There are major two types of data:
1. Quantitative: i.e Numeric (comprises of Integer, Continuous)
2. Qualitative i.e Categorical
This Categorical further divided into 2 types: 1. Nominal 2. Ordinal
According to the nature of data, algorithm is chosen:
Hope! This is useful to you.
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