sklearn.grid_search.GridSearchCV

Examples：

>>>

>>> from sklearn import svm, grid_search, datasets
>>> iris = datasets.load_iris()
>>> parameters = {'kernel':('linear', 'rbf'), 'C':[1, 10]}
>>> svr = svm.SVC()
>>> clf = grid_search.GridSearchCV(svr, parameters)
>>> clf.fit(iris.data, iris.target)
...                             
GridSearchCV(cv=None,
       estimator=SVC(C=1.0, cache_size=..., class_weight=..., coef0=...,
                     degree=..., gamma=..., kernel='rbf', max_iter=-1,
                     probability=False, random_state=None, shrinking=True,
                     tol=..., verbose=False),
       fit_params={}, iid=..., loss_func=..., n_jobs=1,
       param_grid=..., pre_dispatch=..., refit=..., score_func=...,
       scoring=..., verbose=...) 

相關資料：

http://scikit-learn.org/stable/modules/generated/sklearn.grid_search.GridSearchCV.html#sklearn.grid_search.GridSearchCV 

scikit-learn

好用的 machine learning 的工具，scikit-learn

scikit-learn 是python寫的工具
http://scikit-learn.org/stable/

可以安裝在win, mac, linux
安裝的頁面：http://scikit-learn.org/stable/install.html

以下介紹linux安裝的方式：

先裝scikit需要的相關東西 

sudo apt-get install build-essential python-dev python-setuptools \
                     python-numpy python-scipy \
                     libatlas-dev libatlas3gf-base

sudo update-alternatives --set libblas.so.3 \
    /usr/lib/atlas-base/atlas/libblas.so.3
sudo update-alternatives --set liblapack.so.3 \
    /usr/lib/atlas-base/atlas/liblapack.so.3 

sudo apt-get install python-matplotlib

安裝scikit:

1.  用pip

pip install --user --install-option="--prefix=" -U scikit-learn

2. 用apt-get (ubuntu)

sudo apt-get install python-sklearn 

3. 用 yum 

sudo yum install python-scikit-learn