I trained on the following data, and uploaded my Test File to see predictions from the model. The Targets in my data are -1, 0, and 1. But the predictions are fractional numbers, like 0.01, 0.50, etc. I used all defaults on the first model, which had high confidence. I am expecting the predictions to more or less match my original Targets. What am I doing wrong?
Training Data (80,000 rows, only showing Feature 31-35) Training Data (showing last features and target)
Test Data (same, fewer rows)
Test Data for validation
Downloaded predictions from the model after uploading Test Data
Modification: I changed my Target to only predict 1 or 0 so it would run CLASSIFICATION models. After training, I provided the same Test data and the prediction for all rows is 0. This data is sparse, in that there may only be 10 or 20 occurrences of a specific combination of features in the data that predicts a "1". But there are many such combinations in the 80,000 rows. What model should I use to find these sub-predictions?