},
{
'regwgt': 0.01
},
{
'regwgt': 1.0
},
)
numparams = len(parameters)
errors = {}
for learnername in regressionalgs:
errors[learnername] = np.zeros((numparams, numruns))
for r in range(numruns):
trainset, testset = dtl.load_ctscan(trainsize, testsize)
print(('Running on train={0} and test={1} samples for run {2}').format(
trainset[0].shape[0], testset[0].shape[0], r))
for p in range(numparams):
params = parameters[p]
for learnername, learner in regressionalgs.items():
# Reset learner for new parameters
learner.reset(params)
print('Running learner = ' + learnername + ' on parameters ' +
str(learner.getparams()))
# Train model
learner.learn(trainset[0], trainset[1])
# Test model
predictions = learner.predict(testset[0])
error = geterror(testset[1], predictions)
from regressionalgorithms import *
import dataloader
from dataloader import load_ctscan
def l2err(prediction, ytest):
""" l2 error (i.e., root-mean-squared-error) """
return np.linalg.norm(np.subtract(prediction, ytest)) / ytest.shape[0]
#Load the data
error_list = []
for i in range(3):
print("Run=", i + 1)
# We load different samples from the datasets.
train, test = load_ctscan(20000, 10000)
X_train, y_train = train
X_test, y_test = test
# Learn on the features that don't give singular matrix.
linreg = FSLinearRegression({'features': range(69)})
try:
linreg.learn(X_train, y_train)
except np.linalg.linalg.LinAlgError:
continue
y_pred = linreg.predict(X_test)
#Record error
error_list.append(l2err(y_pred, y_test))
plt.plot(linreg.params['features'],
linreg.weights,
label="Run={}".format(i + 1))
""" l2 error squared """
return np.square(np.linalg.norm(np.subtract(prediction,ytest)))
def geterror(predictions, ytest):
# Can change this to other error values
return l2err(predictions,ytest)/ytest.shape[0]
if __name__ == '__main__':
run = True
#common constants and data loaders
trainsize = 1000
testsize = 5000
numparams = 1
numruns = 1
trainset, testset = dtl.load_ctscan(trainsize, testsize)
print('Loading Data...')
while (run == True):
print('1 for 2.a')
print('2 for 2.b')
print('3 for 2.c')
print('4 for 2.d')
print('5 for 2.e')
print('6 for 2.f')
print('7 for 2.g')
print('8 for 2.h')
print('0 for exit')
qnum = input('Enter the question number to run:')
#***********************************************************#
