Rondon7251 score 67
2019/10/25 17:49 投稿
| 機械学習でディープラーニングを実行できない。 |
| 機械学習で次のエラーが出ます。 |
| could not broadcast input array from shape (2,1) into shape (2) |
| /Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: compiletime version 3.6 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.5 |
| return f(*args, **kwds) |
| WARNING:tensorflow:From /Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/backend.py:3086: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. |
| Instructions for updating: |
| keep_dims is deprecated, use keepdims instead |
| WARNING:tensorflow:From /Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/backend.py:1557: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. |
| Instructions for updating: |
| keep_dims is deprecated, use keepdims instead |
| Traceback (most recent call last): |
| File "deep2.py", line 33, in <module> |
| epochs=300) |
| File "/Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/models.py", line 920, in fit |
| validation_steps=validation_steps) |
| File "/Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 1592, in fit |
| batch_size=batch_size) |
| File "/Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 1431, in _standardize_user_data |
| exception_prefix='input') |
| File "/Users/idaryuunosuke/.pyenv/versions/anaconda3-5.3.1/envs/py35/lib/python3.5/site-packages/tensorflow/python/keras/_impl/keras/engine/training.py", line 132, in _standardize_input_data |
| arrays[i] = array |
| ValueError: could not broadcast input array from shape (2,1) into shape (2) |
| 以下コードです |
| ```ここに言語を入力 |
| import tensorflow as tf |
| import tensorflow.contrib.keras as keras |
| from sklearn.model_selection import train_test_split |
| import pandas as pd |
| import numpy as np |
| # データの読み込み --- (*1) |
| analysisresults_data = pd.read_csv("analysis_resultstable_BX.csv",encoding="utf-8") |
| # データをラベルと入力データに分離する |
| y = analysisresults_data.loc[:,["Result"]] |
| x = analysisresults_data.loc[:,["Signatures_id","Hit_count"]] |
| # 学習用とテスト用に分割する --- (*2) |
| x_train, x_test, y_train, y_test = train_test_split(x, y, test_size = 0.2, train_size = 0.8, shuffle = True) |
| # モデル構造を定義 --- (*3) |
| Dense = keras.layers.Dense |
| model = keras.models.Sequential() |
| model.add(Dense(10, activation='relu', input_shape=(1,))) |
| model.add(Dense(1, activation='sigmoid')) # ---(*3a) |
| # モデルを構築 --- (*4) |
| model.compile( |
| loss='categorical_crossentropy', |
| optimizer='adam', |
| metrics=['accuracy']) |
| # 学習を実行 --- (*5) |
| model.fit(x_train, y_train, |
| batch_size=20, |
| epochs=300) |
| # モデルを評価 --- (*6) |
| score = model.evaluate(x_test, y_test, verbose=1) |
| print('正解率=', score[1], 'loss=', score[0]) |
| ``` |
| 何かわかる方いましたら教えてください。 |
