Python report_results Beispiele

Beispiel #1

Datei: predict_model.py Projekt: matthewlw/seizure-forecasting

import sys
sys.path.append('..')
from helpers import load_data_in_chunks, load_model, report_results

(Xs, Ys) = load_data_in_chunks('test', chunk_size=5)
Xs = Xs.reshape(Xs.shape[0], -1)
regr = load_model('linear-multiple')
Ys_pred = regr.predict(Xs)
report_results(Xs, Ys, Ys_pred, 'linear', 'linear-multiple.svg')

Beispiel #2

Datei: predict_model.py Projekt: matthewlw/seizure-forecasting

import sys
sys.path.append('..')
from helpers import load_data_in_chunks, load_model, report_results

(Xs, Ys) = load_data_in_chunks('basic', 'test', chunk_size=5)
Xs = Xs.astype('float32')
Ys = Ys.astype('float32')
regr = load_model('lstm-mse')
Ys_pred = regr.predict(Xs) * 5000
(a, b, c) = Xs.shape
report_results(Xs.reshape(a * b, c), Ys, Ys_pred, 'MSE LSTM', 'lstm-mse.svg')

Beispiel #3

import sys
sys.path.append('..')
from helpers import load_data, load_model, report_results

(Xs, Ys) = load_data('basic', 'test')
regr = load_model('random-forest')
Ys_pred = regr.predict(Xs)
report_results(Xs, Ys, Ys_pred, 'random forest', 'rf.svg')

Beispiel #4

import sys
sys.path.append('..')
from helpers import load_data_in_chunks, load_model, report_results

(Xs, Ys) = load_data_in_chunks('basic', 'test', chunk_size=5)
Xs = Xs.astype('float32')
Ys = Ys.astype('float32')
regr = load_model('conv-custom')
Ys_pred = regr.predict(Xs) * 5000
(a, b, c) = Xs.shape
report_results(Xs.reshape(a * b, c), Ys, Ys_pred, 'convolutional',
               'conv-custom.svg')

Beispiel #5

import sys
sys.path.append('..')
from helpers import load_data_in_chunks, load_model, report_results

(Xs, Ys) = load_data_in_chunks('test', chunk_size=5)
Xs = Xs.astype('float32')
Ys = Ys.astype('float32')
regr = load_model('lstm-custom')
Ys_pred = regr.predict(Xs) * 5000
(a, b, c) = Xs.shape
report_results(Xs.reshape(a * b, c), Ys, Ys_pred, 'LSTM', 'lstm-custom.svg')

Beispiel #6

import sys
sys.path.append('..')
from helpers import load_data, load_model, report_results

(Xs, Ys) = load_data('test')
regr = load_model('linear-basic')
Ys_pred = regr.predict(Xs)
report_results(Xs, Ys, Ys_pred, 'linear', 'linear.svg')

Beispiel #7

Datei: predict_model.py Projekt: matthewlw/seizure-forecasting

import sys
sys.path.append('..')
from helpers import load_data, load_model, report_results

(Xs, Ys) = load_data('basic', 'test')
regr = load_model('dummy')
Ys_pred = regr.predict(Xs)
report_results(Xs, Ys, Ys_pred, 'dummy', 'dummy.svg')

Beispiel #8

Datei: predict_model.py Projekt: Patil-Kranti/seizure-forecasting

import sys
sys.path.append('..')
from helpers import load_data_in_chunks, load_model, report_results

(Xs, Ys) = load_data_in_chunks('test', chunk_size=5)
Xs = Xs.astype('float32')
Ys = Ys.astype('float32')
regr = load_model('conv-mse')
Ys_pred = regr.predict(Xs) * 5000
(a, b, c) = Xs.shape
report_results(Xs.reshape(a * b, c), Ys, Ys_pred, 'convolutional MSE',
               'conv-mse.svg')

Beispiel #9

Datei: predict_model.py Projekt: Patil-Kranti/seizure-forecasting

import sys
sys.path.append('..')
from helpers import load_data, load_model, report_results

import numpy as np

(Xs, Ys) = load_data('test')
regr = load_model('mlp')
Ys_pred = regr.predict(Xs)
report_results(Xs, Ys, Ys_pred, 'multi-layer perceptron', 'mlp.svg')

Beispiel #10

Datei: predict_model.py Projekt: matthewlw/seizure-forecasting

import sys
sys.path.append('..')
from helpers import load_data, load_model, report_results

(Xs, Ys) = load_data('basic', 'test')
regr = load_model('xgb')
Ys_pred = regr.predict(Xs)
report_results(Xs, Ys, Ys_pred, 'gradient boosted', 'xgboost.svg')