Я делаю глубокое обучение, используя Keras в Rstudio. Я копирую и вставляю эту ссылку https://tensorflow.rstudio.com/tutorials/beginners/basic-ml/tutorial_basic_regression/
boston_housing <- dataset_boston_housing()
c(train_data, train_labels) %<-% boston_housing$train
c(test_data, test_labels) %<-% boston_housing$test
paste0("Training entries: ", length(train_data), ", labels: ", length(train_labels))
train_data[1, ] # Display sample features, notice the different scales
library(dplyr)
column_names <- c('CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE',
'DIS', 'RAD', 'TAX', 'PTRATIO', 'B', 'LSTAT')
train_df <- train_data %>%
as_tibble(.name_repair = "minimal") %>%
setNames(column_names) %>%
mutate(label = train_labels)
test_df <- test_data %>%
as_tibble(.name_repair = "minimal") %>%
setNames(column_names) %>%
mutate(label = test_labels)
train_labels[1:10] # Display first 10 entries
spec <- feature_spec(train_df, label ~ . ) %>%
step_numeric_column(all_numeric(), normalizer_fn = scaler_standard())
spec <- fit(spec)
layer <- layer_dense_features(
feature_columns = dense_features(spec),
dtype = tf$float32
)
layer(train_df)
layer(train_df)
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: ('We expected a dictionary here. Instead we got: ', CRIM ZN INDUS CHAS NOX ... TAX PTRATIO B LSTAT label
0 1.23247 0.0 8.14 0.0 0.5380 ... 307.0 21.0 396.90 18.72 15.2
1 0.02177 82.5 2.03 0.0 0.4150 ... 348.0 14.7 395.38 3.11 42.3
**sessionInfo()**
R версия 3.6.3 (2020-02-29) Платформа : x86_64-w64-mingw32 / x64 (64-разрядная версия) Работает в: Windows 10 x64 (сборка 18363)
Продукты матрицы: по умолчанию
языковой стандарт: [1] LC_COLLATE = Spanish_Chile. 1252 LC_CTYPE = Spanish_Chile.1252 LC_MONETARY = Spanish_Chile.1252 [4] LC_NUMERIC = C LC_TIME = Spanish_Chile.1252
прикрепленные базовые пакеты: [1] stats graphics grDevices использует базу данных наборы методов
* 1014 другие прикрепленные пакеты: [1] dplyr_0.8.5 tfdatasets_2.0.0 keras_2.2.5.0 tenorflow_2.0.0
загружен через пространство имен (и не подключен): [1] Rcpp_1.0.3 pillar_1.4.3 compiler_3.6.3 prettyunits_1 .1.1 base64enc_0.1-3 tools_3.6.3
[7] progress_1.2.2 zeallot_0.1.0 digest_0.6.25 packrat_0.5.0 jsonlite_1.6.1valu_0.14
[13] tibble_2.1.3 pkgconfig_2.0.3 rlang_0.4.5 cli_2 .0.2 rstudioapi_0.11 yaml_2.2.1
[19] xfun_0.12 knitr_1.28 generics_0 .0.2 vctrs_0.2.4 rappdirs_0.3.1 hms_0.5.3
[25] tidyselect_1.0.0 reticulate_1.14 glue_1.3.2 forge_0.2.0 R6_2.4.1 fansi_0.4.1
[31] rmarkdown_2.1 purrr_0.3.3 magrittr_1 whisker_0.4 tfestimators_1.9.1 tfruns_1.4
[37] htmltools_0.4.0 assertthat_0.2.1 crayon_1.3.4