is_fp16=args['fp16'], loss_scale=args['loss_scale'], multi_gpu=multi_gpu, multi_label=True) 因为指定了multi_label=True,程序会自己构造模型的头部,以便正确处理多标签分类任务。 训练开始。 这里我们设定跑4个周期(cycle)。 learner.fit(4, lr=args['learning_rate'], schedule_type="warmup_line...
Return_indicator:如果为True,“sparse”则以稀疏的二进制指示器格式返回Y。Allow_unlabeled:如果为True...
Return_indicator:如果为True,“sparse”则以稀疏的二进制指示器格式返回Y。Allow_unlabeled:如果为True...
importtorchimporttorch.nnasnnimporttorch.optimasoptimimporttorchvisionimporttorchvision.transformsastransforms# 定义模型classMultiClassNet(nn.Module):def__init__(self):super(MultiClassNet,self).__init__()self.conv1=nn.Conv2d(3,6,5)self.pool=nn.MaxPool2d(2,2)self.conv2=nn.Conv2d(6,16,5)se...
(y_pred - y_true, 0, 1)), axis=1) fn = backend.sum(backend.round(backend.clip(y_true - y_pred, 0, 1)), axis=1) # calculate precision p = tp / (tp + fp + backend.epsilon()) # calculate recall r = tp / (tp + fn + backend.epsilon()) # calculate fbeta, averaged ...
Bipartion: [false, true, true, false, false, false] Confidences: [0.0, 1.0, 1.0, 0.0, 0.0, 0.0] Ranking: [6, 2, 1, 5, 4, 3] Bipartion: [true, false, false, false, false, true] Confidences: [1.0, 0.0, 0.0, 0.0, 0.0, 1.0] Ranking: [2, 6, 5, 4, 3, 1] Bipartion:...
j_sample= jaccard_score(y_true, y_pred, average='samples') j_micro= jaccard_score(y_true, y_pred, average='micro')### jaccard 算法 ###xx=np.minimum(y_true, y_pred) intersection= np.sum(np.minimum(y_true, y_pred), axis=0) union= ...
name: "resnet101" layer { name: "data" type: "ImageData" top: "data" top: "dummylabel" image_data_param { source: "/path/to/train_imagelist.txt" root_folder: "/path/to/images/" batch_size: 16 new_height: 256 new_width: 256 } transform_param { mirror: true crop_size: 224 ...
URL https://github.com/bearloga/MLPUGS BugReports https://github.com/bearloga/MLPUGS/issues Depends R(>=3.1.2)Suggests knitr,progress,C50,randomForest VignetteBuilder knitr LazyData true License MIT+file LICENSE RoxygenNote5.0.1 NeedsCompilation no Author Mikhail Popov[aut,cre](@bearloga ...
多分类学习(Multi-class):分类器去划分的类别是多个的,但对于每一个样本只能有一个类别,类别间是...