Question: When training a neural network, the loss does not decrease in the few epochs. What could be the reason? 1 ) learning rate is too

When training a neural network, the loss does not decrease in the few epochs. What could be the reason?
1) learning rate is too low
2) regularization parameter is high
3) stuck at local minima
4) it is overtrained

Step by Step Solution

There are 3 Steps involved in it

1 Expert Approved Answer
Step: 1 Unlock blur-text-image
Question Has Been Solved by an Expert!

Get step-by-step solutions from verified subject matter experts

Step: 2 Unlock
Step: 3 Unlock

Students Have Also Explored These Related Databases Questions!

Q:

Part 3 : Regularization In this section we will study the effect of regularization on our predictors. To do this you will need to implement a regularized version of the batch gradient descent learner...

Q:

Jupiter Notebook We have covered some of the limitations of single layer neural networks in class, but they are still powerful learning systems that provide a good way to begin learning about how to...

Q:

Solve all parts with code The google colab code/file is : { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Linear Regression for Red Wine Quality Classification" ] }, {...

Q:

CAN YOU SOLVE BOTH PARTS WITH ACTUAL CODE IN GOOGLE COLAB USING THE . ipynb file copied and pasted below! { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Linear Regression for...

Q:

Hi, Can you please help me with assignment, I am failing to create the train_nn function. Please advise how I can get data to you, my previous efforts have failed. Tensorflow_NeuralNetworkspdf May 1,...

Q:

Keras; Convolutional Neural Network ( CNN ) ; ten - class classifier for CIFAR - 1 0 dataset: Use cifar 1 0 function in keras.datasets to load CIFAR - 1 0 dataset. Split it into the training and...

Q:

Data Mining Review Questions / XLMiner Labs Neural Nets 1. Predicting Prices of Used Cars. The file ToyotaCorolla.xls contains data on used Toyota Corollas for sale during late Summer of 2004 in The...

Q:

Q 8 . Which ones of the following statements are true? ( Check all that apply. ) ( a ) After training a neural network, you observe a large gap between the training accuracy ( 1 0 0 % ) and the test...

Q:

Data Mining Review Questions / XLMiner Labs Neural Nets 1. Predicting Prices of Used Cars. The file ToyotaCorolla.xls contains data on used Toyota Corollas for sale during late Summer of 2004 in The...

Q:

Which of the following gives non-linearity to a neural network? (Choose only one) Stochastic Gradient Descent Rectified Linear Unit Convolution function You are training a neural network and you...

Q:

What is the magnitude of the maximum stress that exists at the tip of an internal crack having a radius of curvature of 2.5 10 -4 mm (10 -5 in.) and a crack length of 2.5 10 -2 mm (10 -3 in.) when...

Q:

A 400-, 2.4-W resistor is needed, but only several 400- , 1.2-W resistors are available (see Exercise 26.10). (a) What two different combinations of the available units give the required resistance...

Q:

Current Attempt in Progress Crane, Inc. dispeses of an unproftable segment of its business. The operation of the segment suffered a $ 3 5 4 0 0 0 loss in the year of disposal. The loss on disposal of...

Q:

last two options for the multiple choice are : performance management development A construction equipment manufacturer, Roswell Corporation, is focusing on becoming a leader in sustainability in...

Q:

Set up a debate between yourself and three other colleagues with two of you arguing in favour of your pay being affected by the performance management scheme and the other two arguing that it should...

Q:

Imagine you are a manager at Sainsburys (case study 5.1) at the meeting where the scheme is being explained. Make a list of questions that you would want to ask to satisfy yourself that the scheme is...

Q:

Discuss with two of your colleagues which benefi ts are the most important ones to offer, putting them in a league table of importance. Justify your decisions.