卷积神经网络的Softmax层的主要功能是??
卷积神经网络的Softmax层的主要功能是??
Softmax回归进行多分类的非线性函数和损失函数分别是什么? A: Softmax函数 B: Sigmoid 函数 C: MSE损失 D: 交叉熵损失
Softmax回归进行多分类的非线性函数和损失函数分别是什么? A: Softmax函数 B: Sigmoid 函数 C: MSE损失 D: 交叉熵损失
Word中插入数学公式的方法是()。 A: "插入"→"形状"→"公式" B: "开发工具"→"公式" C: "插入"→"公式"→"插入新公式" D: "引用"→"插入"→"公式"
Word中插入数学公式的方法是()。 A: "插入"→"形状"→"公式" B: "开发工具"→"公式" C: "插入"→"公式"→"插入新公式" D: "引用"→"插入"→"公式"
逻辑回归和softmax使用的误差准则是
逻辑回归和softmax使用的误差准则是
定义并初始化一个用于存放我们国家的四个直辖市的数组cityName,四个直辖市为:北京,上海,天津,重庆. 正确的是_________ A: String[] cityName=new String[4]{"北京","上海","天津","重庆"}; B: String[] cityName=new String[]{"北京","上海","天津","重庆"}; C: String[] cityName={"北京","上海","天津","重庆"}; D: String cityName = new String[4] { "北京", "上海", "天津", "重庆" };
定义并初始化一个用于存放我们国家的四个直辖市的数组cityName,四个直辖市为:北京,上海,天津,重庆. 正确的是_________ A: String[] cityName=new String[4]{"北京","上海","天津","重庆"}; B: String[] cityName=new String[]{"北京","上海","天津","重庆"}; C: String[] cityName={"北京","上海","天津","重庆"}; D: String cityName = new String[4] { "北京", "上海", "天津", "重庆" };
已知有一个名为names的空列表,如何向其中添加old_driver,rain,jack,shanshan,peiqi,black_girl 元素? A: names.append("old_driver","rain","jack","shanshan","peiqi","black_girl") B: names.extend("old_driver","rain","jack","shanshan","peiqi","black_girl") C: names.insert("old_driver","rain","jack","shanshan","peiqi","black_girl") D: names.extend(["old_driver","rain","jack","shanshan","peiqi","black_girl"])
已知有一个名为names的空列表,如何向其中添加old_driver,rain,jack,shanshan,peiqi,black_girl 元素? A: names.append("old_driver","rain","jack","shanshan","peiqi","black_girl") B: names.extend("old_driver","rain","jack","shanshan","peiqi","black_girl") C: names.insert("old_driver","rain","jack","shanshan","peiqi","black_girl") D: names.extend(["old_driver","rain","jack","shanshan","peiqi","black_girl"])
使用下列代码建立神经网络模型,说法错误的是______。import tensorflow as tfmodel = tf.keras.Sequential()model.add(tf.keras.layers.Flatten( input_shape=(12, )))model.add(tf.keras.layers.Dense(4, activation="relu"))model.add(tf.keras.layers.Dense(3, activation="softmax"))model.summary() A: 该模型含有2个隐含层 B: 该模型输入层和第一隐含层之间有52个可训练参数 C: 该模型隐含层共有4个节点 D: 该模型的输入层共有12个节点
使用下列代码建立神经网络模型,说法错误的是______。import tensorflow as tfmodel = tf.keras.Sequential()model.add(tf.keras.layers.Flatten( input_shape=(12, )))model.add(tf.keras.layers.Dense(4, activation="relu"))model.add(tf.keras.layers.Dense(3, activation="softmax"))model.summary() A: 该模型含有2个隐含层 B: 该模型输入层和第一隐含层之间有52个可训练参数 C: 该模型隐含层共有4个节点 D: 该模型的输入层共有12个节点
以下哪个选项是正确的json数据格式: A: { "id": 2, "userName": admin, "passWord": 12345, "email": admin@qq.com} B: { id: 2, userName: "admin", passWord: "12345", email: "admin@qq.com"} C: { "id": 2, "userName": "admin", "passWord": "12345", "email": "admin@qq.com",} D: { "id": 2, "userName": "admin", "passWord": "12345", "email": "admin@qq.com"}
以下哪个选项是正确的json数据格式: A: { "id": 2, "userName": admin, "passWord": 12345, "email": admin@qq.com} B: { id: 2, userName: "admin", passWord: "12345", email: "admin@qq.com"} C: { "id": 2, "userName": "admin", "passWord": "12345", "email": "admin@qq.com",} D: { "id": 2, "userName": "admin", "passWord": "12345", "email": "admin@qq.com"}
把一个JSON格式数据赋给变量color:color = "色彩":[ "暖色":["红","橙","黄"], "冷色":["青","蓝"], "中性色":["紫","绿","黑","灰","白"] ]以下能够取到冷色“["青","蓝"]”的是哪一个选项?_
把一个JSON格式数据赋给变量color:color = "色彩":[ "暖色":["红","橙","黄"], "冷色":["青","蓝"], "中性色":["紫","绿","黑","灰","白"] ]以下能够取到冷色“["青","蓝"]”的是哪一个选项?_
在Excel中,为表格添加边框的正确的操作是()。 A: 单击"单元格"中的"边框" B: 单击"单元格"中的"边框和底纹" C: 单击"插入"中"边框" D: 单击"插入"中"单元格"
在Excel中,为表格添加边框的正确的操作是()。 A: 单击"单元格"中的"边框" B: 单击"单元格"中的"边框和底纹" C: 单击"插入"中"边框" D: 单击"插入"中"单元格"