Ejemplos de ExplicitMF.score en Python

Ejemplo n.º 1

Archivo: test_grid_search.py Proyecto: arthurmensch/spira

def test_grid_search():
    cv = ShuffleSplit(n_iter=5, random_state=0)
    mf = ExplicitMF(n_components=3, max_iter=10, random_state=0)
    param_grid = {"alpha": [0.1, 1.0, 10]}
    gcv = GridSearchCV(mf, param_grid, cv)
    gcv.fit(X)

    assert_equal(gcv.best_estimator_.alpha, 0.1)
    assert_equal(gcv.best_params_, {"alpha": 0.1})

    mf = ExplicitMF(alpha=0.1, n_components=3, max_iter=10, random_state=0)
    mf.fit(X)

    assert_almost_equal(mf.score(X), gcv.score(X))

Ejemplo n.º 2

def test_grid_search():
    cv = ShuffleSplit(n_iter=5, random_state=0)
    mf = ExplicitMF(n_components=3, max_iter=10, random_state=0)
    param_grid = {"alpha": [0.1, 1.0, 10]}
    gcv = GridSearchCV(mf, param_grid, cv)
    gcv.fit(X)

    assert_equal(gcv.best_estimator_.alpha, 0.1)
    assert_equal(gcv.best_params_, {"alpha": 0.1})

    mf = ExplicitMF(alpha=0.1, n_components=3, max_iter=10, random_state=0)
    mf.fit(X)

    assert_almost_equal(mf.score(X), gcv.score(X))

Ejemplo n.º 3

Archivo: test_matrix_fact.py Proyecto: arthurmensch/spira

def test_matrix_fact_cd():
    # Generate some toy data.
    rng = np.random.RandomState(0)
    U = rng.rand(50, 3)
    V = rng.rand(3, 20)
    X = np.dot(U, V)

    mf = ExplicitMF(n_components=3, max_iter=10, alpha=1e-3, random_state=0,
                    verbose=0)

    mf.fit(X)

    Y = np.dot(mf.P_, mf.Q_)
    Y2 = mf.predict(X).toarray()

    assert_array_almost_equal(Y, Y2)

    rmse = np.sqrt(np.mean((X - Y) ** 2))
    rmse2 = mf.score(X)

    assert_almost_equal(rmse, rmse2)

Ejemplo n.º 4

Archivo: test_matrix_fact.py Proyecto: sungjinlees/spira

def test_matrix_fact_cd():
    # Generate some toy data.
    rng = np.random.RandomState(0)
    U = rng.rand(50, 3)
    V = rng.rand(3, 20)
    X = np.dot(U, V)

    mf = ExplicitMF(n_components=3,
                    max_iter=10,
                    alpha=1e-3,
                    random_state=0,
                    verbose=0)

    mf.fit(X)

    Y = np.dot(mf.P_, mf.Q_)
    Y2 = mf.predict(X).toarray()

    assert_array_almost_equal(Y, Y2)

    rmse = np.sqrt(np.mean((X - Y)**2))
    rmse2 = mf.score(X)

    assert_almost_equal(rmse, rmse2)

Ejemplo n.º 5

Archivo: bench_explicit_mf.py Proyecto: arthurmensch/spira

import sys
import time

from spira.datasets import load_movielens
from spira.cross_validation import train_test_split
from spira.completion import ExplicitMF

try:
    version = sys.argv[1]
except:
    version = "100k"

X = load_movielens(version)
print(X.shape)

X_tr, X_te = train_test_split(X, train_size=0.75, random_state=0)

start = time.time()
mf = ExplicitMF(n_components=30, max_iter=10, alpha=1e-1, random_state=0,
                verbose=1)
mf.fit(X_tr)
print("Time", time.time() - start)
print("RMSE", mf.score(X_te))

Ejemplo n.º 6

Archivo: bench_explicit_mf.py Proyecto: sungjinlees/spira

import sys
import time

from spira.datasets import load_movielens
from spira.cross_validation import train_test_split
from spira.completion import ExplicitMF

try:
    version = sys.argv[1]
except:
    version = "100k"

X = load_movielens(version)
print X.shape

X_tr, X_te = train_test_split(X, train_size=0.75, random_state=0)

start = time.time()
mf = ExplicitMF(n_components=30, max_iter=10, alpha=1e-1, random_state=0,
                verbose=1)
mf.fit(X_tr)
print "Time", time.time() - start
print "RMSE", mf.score(X_te)

Ejemplo n.º 7

Archivo: bench_explicit_mf.py Proyecto: arthurmensch/spira

import sys
import time

from spira.datasets import load_movielens
from spira.cross_validation import train_test_split
from spira.completion import ExplicitMF

try:
    version = sys.argv[1]
except:
    version = "100k"

X = load_movielens(version)
print(X.shape)

X_tr, X_te = train_test_split(X, train_size=0.75, random_state=0)

start = time.time()
mf = ExplicitMF(n_components=30,
                max_iter=10,
                alpha=1e-1,
                random_state=0,
                verbose=1)
mf.fit(X_tr)
print("Time", time.time() - start)
print("RMSE", mf.score(X_te))