model=Sequential([Dense(128,activation='relu',input_shape=(X_train.shape[1],)),Dense(64,activation='relu'),Dense(1,activation='sigmoid')])# 编译模型 model.compile(optimizer='adam',loss='binary_crossentropy',metrics=
监督学习supervised learning:机器学习中最常见的类型,它可以学会将输入数据映射到已知目标annotation。比如回归问题和分类问题(二分类、多分类问题等)是最常见的监督学习的例子。 其他监督学习的应用例子: 序列生成sequence generation 语法树预测syntax tree prediction 目标检测object detection 图像分割image segmentation 分类...
y : array-like of shape (n_samples,) or (n_samples, n_outputs), default=None The target variable to try to predict in the case of supervised learning. groups : array-like of shape (n_samples,), default=None Group labels for the samples used while splitting the dataset into train/tes...
featuring splits in variables which will be important down the tree, are implemented in packageRLT...
1Supervised Learning2Classification3Regression4Measuring performance5Unsupervised Learning6Clustering7Dimensionality Reduction8Density Estimation9Evaluation of Learning Models10Choosing the right algorithmforyour dataset 2.3.1、分类任务(随机梯度下降(SGD)算法) ...
()X_train,X_test,y_train,y_test=train_test_split(data,y,test_size=0.2,random_state=33)X_train.shape,X_test.shape###%%time# 用两行命令进行机器学习xgb=XGBClassifier(objective='binary:logistic',random_state=33,n_jobs=-1)xgb.fit(X_train,y_train)# 对测试数据进行预测xgb_predictions=xgb...
监督式学习(Supervised Learning):给予「有标签」的资料,举例来说:给机器一堆苹果和橘子的照片,并说明哪些是苹果、哪些是橘子,再拿一张新的照片询问机器这是苹果还是橘子,而监督式学习又可分为回归(Regression)和分类(Classification)。 非监督式学习(Unsupervised Learning):给予「无标签」的资料,让机器找出潜在的规则...
SupervisedTuningSpec SyncFeatureViewRequest SyncFeatureViewResponse TFRecordDestination Tensor Overview DataType StructValEntry Tensorboard Overview LabelsEntry TensorboardBlob TensorboardBlobSequence TensorboardExperiment Overview LabelsEntry TensorboardRun Overview LabelsEntry TensorboardTensor Tens...
SupervisedTuningSpec SyncFeatureViewRequest SyncFeatureViewResponse TFRecordDestination Tensor Overview DataType StructValEntry Tensorboard Overview LabelsEntry TensorboardBlob TensorboardBlobSequence TensorboardExperiment Overview LabelsEntry TensorboardRun Overview LabelsEntry TensorboardTensor Tensorboard...
Scikit-learn is known for its ease of use and clean API that simplifies the implementation of bothsupervised and unsupervised learningmethods. Here's what this library offers: Tools for classification (e.g., SVM, decision trees) and regression (e.g., linear regression, ridge regression). ...