Example #13Source File: 04_sent.py From Building-Machine-Learning-Systems-With-Python-Second-Edition with MIT License 6 votes def __grid_search_model(clf_factory, X, Y): cv = ShuffleSplit( n=len(X), n_iter=10, test_size=0.3, indices=True, random_state=0) param_grid = dict(vect...
NOTE that when using custom scorers, each scorer should return a single value. Metric functions returning a list/array of values can be wrapped into multiple scorers that return one value each. See :ref:`multimetric_grid_search` for an example. If None, the estimator's score method is used...
Example #1Source File: hpc_svm.py From cwcf with MIT License 8 votes def get_full_rbf_svm_clf(train_x, train_y, c_range=None, gamma_range=None): param_grid = dict(gamma=gamma_range, C=c_range) cv = StratifiedShuffleSplit(n_splits=2, test_size=0.2, random_state=42) grid =...
NOTE that when using custom scorers, each scorer should return a single value. Metric functions returning a list/array of values can be wrapped into multiple scorers that return one value each. See :ref:`multimetric_grid_search` for an example. If None, the estimator's default scorer (if ...
See :ref:`multimetric_grid_search` for an example. If None, the estimator's score method is used. n_jobs : int, default=None. Number of jobs to run in parallel. ``None`` means 1 unless in a :obj:`joblib.parallel_backend` context. ``-1`` means using all processors. See :term...
File: /home/jacob04/opt/python/numpy/numpy-1.7.1/lib/python2.7/site- packages/numpy/__init__.py Docstring: <no docstring> Class Docstring: ndarray(shape, dtype=float, buffer=None, offset=0, strides=None, order=None) > ?X Type: ndarray ...
前文回顾: 在Python中开始使 scikit-learn 框架提供了搜索参数组合的功能。 此功能在 GridSearchCV 类中提供,可用于发现配置模型以获得最佳表现的最佳方法。...= [2, 4, 6, 8] 3param_grid = dict(max_depth=max_depth, n_estimators=n_estimators) 然后使用 10 倍交叉验证评估每个参数组合...neg_log_...
这将使用完整数据集和找到的最佳参数运行最终训练步骤。要找到最佳参数，GridSearchCV显然没有使用整个数据...
each with a different set of hyper-parameters. Each of these parameter combinations that correspond to a single model is said to lie on a “grid” point. The purpose is to train and evaluate each of these models using cross-validation, for example. Then you choose the one that performed ...
NOTE that when using custom scorers, each scorer should return a single value. Metric functions returning a list/array of values can be wrapped into multiple scorers that return one value each. See :ref:`multimetric_grid_search` for an example. If None, the estimator's default scorer (if ...