进一步,再来实现self-training模型的拟合部分,代码如下: 1 def fit(self, X, y): 2 if not (0 <= self.threshold < 1): 3 raise ValueError("参数 threshold 必须属于 [0,1) 的范围" 4 f",当前传入为 {self.threshold}") 5 has_label = y != -1 6 if np.all(has_label): # 如果全都有...
Self-training 的目标是从未标注数据中提取信息,节省标注成本。 简单易实现 不需要复杂的模型结构或训练流程,只需调整置信度阈值和迭代机制。 灵活性强 可以与任何监督学习模型(如 SVM、随机森林或深度神经网络)结合使用。 3. 示例:具体实现流程(伪代码) 假设有一个二分类任务 from sklearn.ensemble import RandomFo...
现在让我们使用 Sklearn 的SelfTrainingClassifier,同时使用相同的 SVC 模型作为基础估计器。作为Sklearn的一部分SelfTrainingClassifier支持与任何兼容sklearn标准的分类模型进行整合。 代码语言:javascript 复制 ### Step1-Data Prep ### # Select dataformodeling-we are includingmasked(-1)labelsthistime X_train=d...
几篇论文实现代码:《On Self-Contact and Human Pose》(ICCV 2021) GitHub:https:// github.com/muelea/tuch [fig1] 《Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-iden...
1defmultihead_attention(self, queries,2keys,3num_units=None,4num_heads=8,5dropout_rate=0,6is_training=True,7causality=False,8scope="multihead_attention",9reuse=None):10'''11June 2017 by kyubyong park.12kbpark.linguist@gmail.com.13https://www.github.com/kyubyong/transformer14'''15'''...
《TransFace: Calibrating Transformer Training for Face Recognition from a Data-Centric Perspective》(ICCV 2023) GitHub: github.com/DanJun6737/TransFace《PhonMatchNet: Phoneme-Guided Zero-Shot Keyword Spotting for User-Defined Keywords》(INTERSPEECH 2023) GitHub: github.com/ncsoft/PhonMatchNet...
if self.training and not torch.jit.is_scripting(): # during inference, return the average of both classifier predictions return x, x_dist else: return (x + x_dist) / 2 else: # 对应最后Linear 全连接层 x = self.head(x) return x ...
SapBERT: Self-alignment pretraining for BERT的代码使用示例,【代码】SapBERT:Self-alignmentpretrainingforBERT的代码使用示例。
DiT: self-supervised pre-training for Document Image Transformers TextDiffuser/TextDiffuser-2(NEW): Diffusion Models as Text Painters WavLM: speech pre-training for full stack tasks VALL-E: a neural codec language model for TTS LayoutLM/LayoutLMv2/LayoutLMv3: multimodal (text + layout/format + ...