๐ธThe quality & quantity of data available for training & testing play significant role in determining the performance of ML model
๐ธML algorithm use data to learn pattern & relationship between input variable target output whch can be used for prediction or classification tasK
๐ธData can be divided into training and testing sets. The training set is used to train the model, and the testing set is used to evaluate the performance of the model. It is important to ensure that the data is split in a random and representative way.
Topic -- EDA using Bivariate and Multivariate Analysis
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โ Bivariate Analysis
Bi means two and variate means variable, so here there are two variables. The analysis is related to cause and the relationship between the two variables.
Three types -
๐ธScatter Plot
๐ธLinear Correlation
๐ธChi-square Test
โ Multivariate analysis :
is required when more than two variables have to be analyzed simultaneously.
๐ธUni means one and variate means variable, so in univariate analysis, there is only one dependable variable. The objective of univariate analysis is to derive the data, define and summarize it, and analyze the pattern
๐ธUnivariate data can be described through:
- ร Frequency Distribution Tables
ร Bar Charts
ร Histograms
ร Pie Charts