对于任何Keras层(Layer类),可有人解释如何理解之间的区别input_shape,units,dim,等?
例如,doc说明了units指定图层的输出形状.
在神经网络的图像下面hidden layer1有4个单位.这是否直接转换为对象的units属性Layer?或者units在Keras中,隐藏层中每个权重的形状是否等于单位数?
有没有办法将当前的 conda 基础(根)环境(当前有 Python 3.8.11)更新为 Python 3.9 或 3.10?我知道使用新的虚拟环境是推荐的方法,但我仍然想学习如何操作。
我尝试使用conda install python=3.9and conda install python=3.10,这是几年前一些帖子推荐的,但它们不起作用,最终出现以下错误
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to …Run Code Online (Sandbox Code Playgroud) 如何编写规范以检查用户注册成功后是否在数据库中创建了新记录?在raails 4中使用rspec与capybara,factorygirl和database_cleaner gems.
我觉得这种情况很常见,答案应该很容易找到,但我无法在这里或通过谷歌找到.
我正在尝试使用 category_encoders.OrdinalEncoder 将类别映射到熊猫数据框中的整数。但是我在没有任何其他有用提示的情况下收到以下错误。
TypeError: 'NoneType' object is not iterable
Run Code Online (Sandbox Code Playgroud)
代码在没有尝试映射的情况下运行良好,但我想要映射。
代码:
import category_encoders as ce
ordinal_cols = [
"ExterQual",
]
ordinal_cols_mapping = [{
"ExterQual": {
'Ex': 5,
'Gd': 4,
'TA': 3,
'Fa': 2,
'Po': 1,
'NA': NaN
}},
]
encoder = ce.OrdinalEncoder( mapping = ordinal_cols_mapping, return_df = True, cols = ordinal_cols,)
df_train = encoder.fit_transform(train_data)
print(df_train)
Run Code Online (Sandbox Code Playgroud)
我做错了什么?
映射:字典列表 用于编码的类到标签的映射,可选。
http://contrib.scikit-learn.org/categorical-encoding/ordinal.html
全栈跟踪:
---------------------------------------------------------------------------
TypeError
Traceback (most recent call last)
<ipython-input-56-4944c8d41d07> in <module>()
150 # use the Ordinal Encoder to map the ordinal …Run Code Online (Sandbox Code Playgroud) encoding machine-learning ordinal scikit-learn sklearn-pandas
我查看了几个教程,ruby指南和几个stackoverflow问题.我首先尝试使用simple_form,现在是老式的方式,无法弄清楚为什么params没有通过.
控制器:
def new
@topgem = Topgem.new
end
def create
@topgem = Topgem.new(topgem_params)
if @topgem.save
redirect_to @topgem
else
render 'new'
end
Run Code Online (Sandbox Code Playgroud)
...
private
def topgem_params
params.require(:name).permit(:url, :description, :downloads, :last_updated)
end
Run Code Online (Sandbox Code Playgroud)
模型:
class Topgem < ActiveRecord::Base
has_many :votes
has_many :users, through: :votes
validates :name, presence: true, uniqueness: true, :length => {
:minimum =>2,
:maximum =>50}
validates :url, presence: true
validates :description, presence: true
validates :downloads, numericality: { only_integer: true }
end
Run Code Online (Sandbox Code Playgroud)
new.html.erb
<%= form_for(@topgem) do |f| %>
<%= f.label :name %>: …Run Code Online (Sandbox Code Playgroud) 我有一个当前有形式的columne myVar REAL NOT NULL.这应该只是一个实际的数字.我可以添加什么样的约束来防止myVar成为NaN?
anaconda ×1
conda ×1
constraints ×1
encoding ×1
keras ×1
keras-layer ×1
nan ×1
ordinal ×1
postgresql ×1
python ×1
python-3.x ×1
rspec ×1
ruby ×1
scikit-learn ×1
tensor ×1