cv_svc_ts_custom.py

import numpy as np
import os,sys
module_path = os.path.abspath(os.path.join('../'))
if module_path not in sys.path:
    sys.path.append(module_path)
from ts import *
from custom_svc import *
import copy
import NN,time
from custom_gridsearch import GridSearch
import sys

number=sys.argv[1]
alpha=[float(a) for a in sys.argv[2].split(',')]
eps=[float(a) for a in sys.argv[3].split(',')]

#alpha=float(sys.argv[2])
#eps=float(sys.argv[3])


path='./data/UCR_TS_Archive_2015/Trace/'
train=create_ts(path,t='TRAIN')
test=create_ts(path,t='TEST')
x_train,y_train=zip(*train)
x_test,y_test=zip(*test)


n_splits=5
n_jobs=1

tuned_parameters = [{'epsilon':list(eps),
                    'alpha':list(alpha)
                     ,'method':['sqeuclidean']
                     ,'normalize_distance':[True]
                     ,'features_metric':['sqeuclidean']
                     ,'scale':[False,True]
                     ,'C':[10**k for k in [0,0.5,1,1.7,1.8,2,2.1,2.2,2.3,2.22,2.23,2.24,2.25,2.26,2.28,2.29,2.3,2.32,2.33,2.34,2.35,2.36,2.4]]
                     ,'gamma':[2**k for k in [-3,-2,-1,-1.2,-1.1,-1.3,-1.4,-0.1,-0.2,-0.3,-0.4,0,0.01,0.02,0.03,0.04,0.05,0.06,0.1,0.2,0.3,0.4,0.5,0.6,1,2,3]]}]



graph_svc=TS_WGW_SVC_Classifier()
clf = GridSearch(graph_svc, tuned_parameters=tuned_parameters,nb_splits=n_splits,n_jobs=n_jobs,parallel=False,csv='result_'+str(number)+'.csv')
clf.fit(np.array(x_train).reshape(-1,1),np.array(y_train))


preds=clf.test_best_estimator(np.array(x_train).reshape(-1,1),np.array(y_train),np.array(x_test).reshape(-1,1),np.array(y_test))