Create ML Model using Python
- Status: Closed
- Prize: $150
- Entries Received: 10
- Winner: yatishdua
Contest Brief
I need a Machine Learning model to classify the probability of success of the events Y in the spreadsheet attached based on the variables X for each event on the same spreadsheet.
Y is a random variable (Y=1 for success or Y=0 for failure) that is influenced by the X variables. Ideally each event should be classified in 1 of 7 classes, being the middle class 0 representing that the event has the same probability of the average of all events (around 36,5%). Higher class, (+1, +2, +3) should show an increased probability of success while lower classes( -1, -2, -3) should have a lower probability. (The classification model and/or number of classes is open for suggestion).
The best model will be chosen based on its capability to differentiate events with lower probabilities from the ones with higher probabilities of success. For example, class -3, will be better of the more events it has and the lower probability of success it has. Class +3 on the other side should also have the most events possible , but with the highest probability of success. Class 0 should have the fewest events and be around the dataset average.
I also attached a spreadsheet with an example of the desired outcome. The example should not be used as a target, but only as a reference of the desired output. I believe the outputs of the example could be improved.
Make sure the model is not overfitting the data. The models will be tested against another set of the same data that is not included in the spreadsheet.
I require the model to be implemented in python. Tensorflow is optional, but preferred.
Recommended Skills
Employer Feedback
“He delivery the solution as requested.”
bddmendonca, Brazil.
Top entries from this contest
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yatishdua India
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meghraj9 India
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meghraj9 India
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yatishdua India
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meghraj9 India
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vijaykrishna0497 India
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vijaykrishna0497 India
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vijaykrishna0497 India
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vijaykrishna0497 India
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vijaykrishna0497 India
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