Open ipashchenko opened 8 years ago
Commit bb869a3d7421936c0a44a9a611067da627ede49a uses this features:
prop.area, gg.amplitude.value, abs(gg.x_stddev.value), abs(gg.y_stddev.value), abs(gg.theta.value), abs(gg.x_stddev.value/gg.y_stddev.value), prop.extent, abs(gg.amplitude/prop.mean_intensity), prop.solidity, prop.major_axis_length, prop.minor_axis_length, prop.perimeter, prop.max_intensity, prop.mean_intensity, prop.weighted_moments_hu[0], prop.weighted_moments_hu[1], prop.weighted_moments_hu[2], prop.orientation, prop.inertia_tensor_eigvals[0], prop.inertia_tensor_eigvals[1], prop.filled_area, prop.euler_number, prop.eccentricity, prop.convex_area
Only 3-4 of them are informative as GBC
shows.
EDIT:
Feature importance : [ 0. 0.18400372 0. 0.01957175 0. 0. 0.
0.11580235 0. 0. 0. 0. 0.21075891
0.23584882 0.06206432 0.04069084 0. 0. 0. 0.
0. 0. 0.13125928 0. ]
Currently only 9 and only 2-3 of them are informative (for GBC). Should i use feature selection or let the algo decide what are the most informative ones (like GBC)?