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import os
import pandas as pd
import numpy as np
import pprint
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os.environ['OCTAVE_EXECUTABLE'] = "C:/Octave/Octave-4.2.1/bin/octave-cli-4.2.1.exe"
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%load_ext oct2py.ipython
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from oct2py import octave
_ = octave.addpath('LOFS_Octave/source_codes/')
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x = np.array([[1, 2], [3, 4]], dtype=float)
out, oclass = octave.roundtrip(x)
pprint.pprint([x, x.dtype, out, oclass, out.dtype])
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def train_label(fname):
targetname = fname.replace(".csv", ".labels")
return pd.read_csv(targetname)
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fpath = 'uci\\spectf_train.csv'
spectf_train = np.array(pd.read_csv(fpath))
target = np.array(train_label(fpath)).flatten()
spectf = np.hstack([target.reshape(-1, 1), spectf_train])
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spect = octave.load('spect.mat')
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alpha_invest_feats = octave.Alpha_Investing(spectf_train, target.reshape(-1, 1))
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alpha_invest_feats
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%octave_push spectf
%octave_pull spectf
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osfs_feats = octave.fast_osfs_z(spectf, 1, 0.05)
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osfs_feats
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wdbc = octave.load('wdbc.mat')
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osfs_feats = octave.fast_osfs_z(wdbc['wdbc'], 31, 0.00000001)
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np.array(1).flatten()
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osfs_feats.flatten()
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from sklearn import datasets
iris = datasets.load_iris()
iris_train = np.hstack([iris.target.reshape(-1, 1), iris.data[:, [0]]])
In [167]:
X = spectf_train
y = target
alpha = 0.05
X_train = np.hstack([y.reshape(-1, 1), X])
osfs_feats = octave.fast_osfs_z(X_train, 1, alpha)
feats_fix = [int(x-1) for x in list(np.array(osfs_feats).flatten())]
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feats_fix
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