Goal: The program chooses an appropriate ML model (regression, classification, clustering) and executes on a given target variable to make predictions based on any given csv data set.
- We will preprocess a CSV file using pandas:
- label each column data type (nominal, continuous, binary)
- Remove / impute NA value
- We will ask For a "guess" column
- make a guess using sklearn:
- We go to each row, compare it to each other row, and find 3NN
- We will have to check the column type we adding the points up
- top N rows give us an output type. If Binary, make bindary guess. Otherwise average