7.1 Embedding [source] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 5.8 融合层 Merge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 5.8.1 Add [source] Theoretically Grounded Application of Dropout in Recurrent Neural Networks 关于 KERAS 网络层 104 5.8 融合层 Merge 5.8.1 Add [source] keras.layers.Add() 计算一个列表的输入张量的和。 相加层接受一个列表的张量，所有的张量必须有相同的输入尺寸，然后返回一个张量（和 Bidirectional [source] keras.layers.Bidirectional(layer, merge_mode='concat', weights=None) RNN 的双向封装器，对序列进行前向和后向计算。 参数 • layer: Recurrent 实例。 • merge_mode: 前向和后向 RNN 的输出的结合模式。为 {’sum’, ’mul’, ’concat’,

Clustering 1 Start with each example in its own singleton cluster 2 At each time-step, greedily merge 2 most similar clusters 3 Stop when there is a single cluster of all examples, else go to 2 Feng is usually more efficient run-time wise Hierarchical clustering can be slow (has to make several merge/split decisions) No clear consensus on which of the two produces better clustering Feng Li (SDU)

........................................................................................... 47 Merge Layer ........................................................................................... refers the input dimension.  input_length refers the length of input sequence. Merge Layer It is used to merge a list of inputs. It supports add(), subtract(), multiply(), average(), maximum(),

拼接与拆分 主讲人：龙良曲 Merge or split https://blog.openai.com/generative-models/ ▪ Cat ▪ Stack ▪ Split ▪ Chunk cat ▪ Statistics about scores ▪ [class1-4, students, scores] ▪ [class5-9, students, scores]

train-val-test K-fold cross-validation Train Set Test Set Val Set k-fold cross validation ▪ merge train/val sets ▪ randomly sample 1/k as val set 下一课时 减轻Overfitting Thank You.

col_label] 通过标签选取行/列 df.iloc[row_loc, col_loc] 通过位置（自然数）选取行/列 65 Python模块-Pandas ⚫ 数据合并 pd.merge(left, right) 类数 据库的数据融合操作. 参数：how，融合方式，包括左连接、右连接、内连 接（默认）和外连接；on，连接键；left_on，左 键；right_on，右键；left_index，是否将left

col_label] 通过标签选取行/列 df.iloc[row_loc, col_loc] 通过位置（自然数）选取行/列 66 Python模块-Pandas ⚫ 数据合并 pd.merge(left, right) 类数 据库的数据融合操作. 参数：how，融合方式，包括左连接、右连接、内连 接（默认）和外连接；on，连接键；left_on，左 键；right_on，右键；left_index，是否将left

return max(pairs, key=pairs.get) # 具有最大值的“pairs”键 作为基于连续符号频率的贪心方法，字节对编码将使用以下merge_symbols函数来合并最频繁的连续符号对 以产生新符号。 def merge_symbols(max_freq_pair, token_freqs, symbols): symbols.append(''.join(max_freq_pair)) = 10 for i in range(num_merges): max_freq_pair = get_max_freq_pair(token_freqs) token_freqs = merge_symbols(max_freq_pair, token_freqs, symbols) print(f'合并# {i+1}:',max_freq_pair) 合并# 1: ('t', 'a')