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Create a decision tree based on the table, calculate the first tree separation in decision tree which attribute to start based on GINI or ENTROPY index depending on your choice. You

Create a decision tree based on the table, calculate the first tree separation in decision tree which attribute to start based on GINI or ENTROPY index depending on your choice. You

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Assuming that you are the quality engineer in a composite manufacturing process. You are producing different products in two different classes with the following properties as tensile strength and shear stress as given. Please explain your machine learning approach and test for the new product data with Tensil =4, Shear=6. Is it going to be supervised or unsupervised. + Tensil Shear Class Product 1 1 3 1 Product 2 2 2 Product 3 4 4 1 Product 4 1 Product 5 Product 6 6. 10 2
Transcribed Image Text:Assuming that you are the quality engineer in a composite manufacturing process. You are producing different products in two different classes with the following properties as tensile strength and shear stress as given. Please explain your machine learning approach and test for the new product data with Tensil =4, Shear=6. Is it going to be supervised or unsupervised. + Tensil Shear Class Product 1 1 3 1 Product 2 2 2 Product 3 4 4 1 Product 4 1 Product 5 Product 6 6. 10 2
Create a decision tree based on the table, calculate the first tree separation in decision tree which attribute to start based on GINI or ENTROPY index depending on your choice. You can test binary or multiway splits.Chose which one is performing better. It is expected that you compare two splits at least based on different properties. And please remember identification columns never used in Machine Learning Tid Age Car Type Class 23 Family High High High 1 17 Sports 43 Sports 3 68 Family Low 4 32 Truck Low 20 Family High
Transcribed Image Text:Create a decision tree based on the table, calculate the first tree separation in decision tree which attribute to start based on GINI or ENTROPY index depending on your choice. You can test binary or multiway splits.Chose which one is performing better. It is expected that you compare two splits at least based on different properties. And please remember identification columns never used in Machine Learning Tid Age Car Type Class 23 Family High High High 1 17 Sports 43 Sports 3 68 Family Low 4 32 Truck Low 20 Family High
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