GitHub - vanshshah/TEAM-MINER: The objective of this project is to predict whether the car you are planning to buy in the auction is a bad buy or not. This will increase the profits and decrease the risk of the car merchants who are planning to buy a car in the auction. Build a model for prediction with test and training data and check which would provide more accurate results.

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The objective of this project is to predict whether the car you are planning to buy in the auction is a bad buy or not. This will increase the profits and decrease the risk of the car merchants who are planning to buy a car in the auction. Build a model for prediction with test and training data and check which would provide more accurate results.

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
K means		K means
SVM		SVM
ReadMe.txt		ReadMe.txt

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Steps to run K means:

Step 1:
Copy the project into local disk

Step 2:
Open the project location in Jupyter Notebook

Step 3:
Naviagte to folder K Means and run the 'preprocessing.ipynb' (shortcut to run "Shift+Enter") file

Step 4:
Now there should be a csv file named preprocessed_data in the folder named data.

Step 5:
As per your required input change the values in Input.txt.

Step 6:
In OuputGeneration.ipynb, Number of clusters can be changed as per requirement for the variable ks

Step 7:
Execute 'OutputGeneration.ipynb' (shortcut to run Shift+Enter)

Step 8:
The accuracy.csv file will be generated in the output folder. This will give accuracy and time taken to run for each of the input specified.

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Steps to run SVM: