I have two 1:1 arrays of data, that can be plotted on a Cartesian x and y graph. These two arrays represent one sample to then predict later.
# data structure with two dimensions, x and y
sample[0] = [1, 2, 3]
sample[1] = [5, 5, 5]
How can I shape this feature input (x and y) with Python for a machine learning features table: (features.csv)
Not sure about this part:
feature1, feature2, feature3
'(1, 5)', '(2, 5)', '(3, 5)'
Can I do x * y simply for each?
For more info the target format (targets.csv):
class a
class b
I have a working example with 1D features. This is the 1D example: https://github.com/amstuta/random-forest
I'm trying to use a Cartesian 2D input of x and y, instead of 1D for each feature.