首页 人工智能 机器学习     /    SKlearn工具箱matlab版

SKlearn工具箱matlab版

上传者: wq4xes28 | 上传时间:2017/8/13 13:02:31 | 文件大小:29KB | 文件类型:zip
SKlearn工具箱matlab版
SKlearn工具箱matlab版本,可供调试,喜欢的科研下载,用于深度学习,机械学习

文件下载

资源详情

[{"title":"(40个子文件29KB)SKlearn工具箱matlab版","children":[{"title":"steven2358-sklearn-matlab-9612feb","children":[{"title":"lib","children":[{"title":"ensemble","children":[{"title":"GradientBoostingRegressor.m <span style='color:#111;'>1.64KB</span>","children":null,"spread":false}],"spread":true},{"title":"metrics","children":[{"title":"r2_score.m <span style='color:#111;'>1.15KB</span>","children":null,"spread":false},{"title":"pairwise","children":[{"title":"rbf_kernel.m <span style='color:#111;'>729B</span>","children":null,"spread":false},{"title":"linear_kernel.m <span style='color:#111;'>252B</span>","children":null,"spread":false},{"title":"euclidean_distances.m <span style='color:#111;'>529B</span>","children":null,"spread":false},{"title":"pairwise_kernels.m <span style='color:#111;'>2.40KB</span>","children":null,"spread":false},{"title":"polynomial_kernel.m <span style='color:#111;'>1.05KB</span>","children":null,"spread":false}],"spread":true},{"title":"mean_squared_error.m <span style='color:#111;'>569B</span>","children":null,"spread":false}],"spread":true},{"title":"tools","children":[{"title":"dist2.m <span style='color:#111;'>716B</span>","children":null,"spread":false}],"spread":true},{"title":"pipeline","children":[{"title":"make_pipeline.m <span style='color:#111;'>459B</span>","children":null,"spread":false},{"title":"Pipeline.m <span style='color:#111;'>2.03KB</span>","children":null,"spread":false}],"spread":true},{"title":"BaseEstimator.m <span style='color:#111;'>1.12KB</span>","children":null,"spread":false},{"title":"decomposition","children":[{"title":"PCA_.m <span style='color:#111;'>1.04KB</span>","children":null,"spread":false}],"spread":true},{"title":"cluster","children":[{"title":"KMeans_.m <span style='color:#111;'>2.63KB</span>","children":null,"spread":false}],"spread":true},{"title":"linear_model","children":[{"title":"Ridge.m <span style='color:#111;'>861B</span>","children":null,"spread":false},{"title":"LinearRegression.m <span style='color:#111;'>950B</span>","children":null,"spread":false},{"title":"Lasso_.m <span style='color:#111;'>990B</span>","children":null,"spread":false},{"title":"LogisticRegression.m <span style='color:#111;'>1.18KB</span>","children":null,"spread":false},{"title":"log_cost_function_reg.m <span style='color:#111;'>890B</span>","children":null,"spread":false}],"spread":true},{"title":"cross_validation","children":[{"title":"train_test_split.m <span style='color:#111;'>445B</span>","children":null,"spread":false}],"spread":true},{"title":"preprocessing","children":[{"title":"LabelBinarizer.m <span style='color:#111;'>1.75KB</span>","children":null,"spread":false},{"title":"MinMaxScaler.m <span style='color:#111;'>2.39KB</span>","children":null,"spread":false},{"title":"StandardScaler.m <span style='color:#111;'>2.02KB</span>","children":null,"spread":false},{"title":"FunctionTransformer.m <span style='color:#111;'>998B</span>","children":null,"spread":false}],"spread":true},{"title":"RegressorMixin.m <span style='color:#111;'>1.35KB</span>","children":null,"spread":false},{"title":"kernel_ridge","children":[{"title":"KernelRidge.m <span style='color:#111;'>2.75KB</span>","children":null,"spread":false}],"spread":true}],"spread":false},{"title":"install.m <span style='color:#111;'>324B</span>","children":null,"spread":false},{"title":"demo","children":[{"title":"demo_logistic_regression.m <span style='color:#111;'>597B</span>","children":null,"spread":false},{"title":"demo_label_binarizer.m <span style='color:#111;'>458B</span>","children":null,"spread":false},{"title":"demo_pca.m <span style='color:#111;'>328B</span>","children":null,"spread":false},{"title":"demo_kmeans.m <span style='color:#111;'>399B</span>","children":null,"spread":false},{"title":"data","children":[{"title":"sklearn_data_2clusters.m <span style='color:#111;'>471B</span>","children":null,"spread":false},{"title":"sklearn_data_noisyplane.m <span style='color:#111;'>539B</span>","children":null,"spread":false},{"title":"sklearn_data_3clusters.m <span style='color:#111;'>583B</span>","children":null,"spread":false}],"spread":true},{"title":"demo_ridge_regression.m <span style='color:#111;'>608B</span>","children":null,"spread":false},{"title":"run_all_demos.m <span style='color:#111;'>664B</span>","children":null,"spread":false},{"title":"demo_kernel_ridge_regression.m <span style='color:#111;'>1.22KB</span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'>2.65KB</span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'>74B</span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'>205B</span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【好快吧下载】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【好快吧下载】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【好快吧下载】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,8686821#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明