大規模線性分類、回歸和排序用的python庫：lightning

python下大規模線性分類、回歸和排序用的庫，支持SDCA、Prox-SDCA、SGD, AdaGrad, SAG, SVRG、FISTA, SpaRSA，亮點：和scikit-learn使用相同的API約定、原生支持數據的密集和稀疏表示、計算密集模塊用Cython開發。

Highlights:

• follows the scikit-learn API conventions
• supports natively both dense and sparse data representations
• computationally demanding parts implemented in Cython
</ul>

Solvers supported:

• primal coordinate descent
• dual coordinate descent (SDCA, Prox-SDCA)
• SGD, AdaGrad, SAG, SVRG
• FISTA, SpaRSA

from sklearn.datasets import fetch_20newsgroups_vectorized
from lightning.classification import CDClassifier

# Load News20 dataset from scikit-learn.
bunch = fetch_20newsgroups_vectorized(subset="all")
X = bunch.data
y = bunch.target

# Set classifier options.
clf = CDClassifier(penalty="l1/l2",
                   loss="squared_hinge",
                   multiclass=True,
                   max_iter=20,
                   alpha=1e-4,
                   C=1.0 / X.shape[0],
                   tol=1e-3)

# Train the model.
clf.fit(X, y)

# Accuracy
print clf.score(X, y)

# Percentage of selected features
print clf.n_nonzero(percentage=True)




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