Which of the following activation functions is primarily used for neural networks designed to classify binary data?a)Hyperbolic tangent (tanh) functionb)Sigmoid functionc)Rectified Linear Unit (ReLU)d)Softmax function
Question
Which of the following activation functions is primarily used for neural networks designed to classify binary data?a)Hyperbolic tangent (tanh) functionb)Sigmoid functionc)Rectified Linear Unit (ReLU)d)Softmax function
Solution
The Sigmoid function is primarily used for neural networks designed to classify binary data. This is because the Sigmoid function outputs a value between 0 and 1, which can be treated as a probability for binary classification problems. Here's a step-by-step explanation:
-
The Sigmoid function is defined as 1 / (1 + e^-x). This function takes any real-valued number and maps it into a value between 0 and 1.
-
In the context of binary classification in neural networks, these output values can be interpreted as the probability that a given input point belongs to a certain class.
-
For example, if the output of the Sigmoid function is greater than or equal to 0.5, we can classify the input point as belonging to class 1. If the output is less than 0.5, we can classify the input point as belonging to class 0.
-
This makes the Sigmoid function suitable for binary classification problems. Other activation functions like the Hyperbolic tangent function or the Rectified Linear Unit function do not have this property, and the Softmax function is more suitable for multi-class classification problems.
Similar Questions
Suppose we use a neural network to classify images of handwritten digits (0-9). Which of the following activation functions is most suitable at the output layer? Softmax ReLU Tanh Sigmoid
Which of the following is NOT a common activation function used in ANNs?a.Tanh (Hyperbolic Tangent)b.Sigmoidc.ReLU (Rectified Linear Unit)d.Euclidean
The ______________ function is often used as an activation function in the output layer of a binary classification problem.
A fixed income analyst is trying evaluating the probablity of default of a high yield bond using a neural network. Which type of activation function would he be LEAST likely to use?ALinear functionBLogistic functionCHyperbolic functionDRELU Function
8. A machine learning specialist is training a deep neural network to classify an image into one of the 4 categories available. Which of the following is the best activation functions the specialist can use in the output neuron?softmaxrelusigmoidlinear9. import pandas as pddf =pd.DataFrame( { 'Name': ['Alice', 'Bob', 'Charlie', 'Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35, 25, 30, 35], 'City': ['New York', 'Los Angeles', 'Chicago', 'New York', 'Los Angeles', 'Chicago'], 'Salary': [70000, 80000, 90000, 75000, 85000, 95000]})Which of the following code snippets correctly calculates the average salary for each city?df.groupby('City').Salary.mean()All of the aboveNone of the abovedf.groupby('City', as_index=False)['Salary'].mean()df.groupby('City').agg({'Salary': 'mean'})df.groupby('City')['Salary'].mean()
Upgrade your grade with Knowee
Get personalized homework help. Review tough concepts in more detail, or go deeper into your topic by exploring other relevant questions.