All Questions
Tagged with sgd machine-learning
9 questions
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How to calculate gradient of MSE in backpropagation? [duplicate]
I want to implement a neural network from scratch to solve linear regression by using backpropagation. I don't understand how to compute the gradient of the MSE cost function with respect to each ...
- 152
1
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1k
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Understanding SGD for Binary Cross-Entropy loss
I'm trying to describe mathematically how stochastic gradient descent could be used to minimize the binary cross entropy loss.
The typical description of SGD is that I can find online is: $\theta = \...
- 13
1
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1
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30
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Understanding Learning Rate in depth
I am trying to understand why the learning rate does not work universally. I have two different data sets and have tested out three learning rates 0.001 ,0.01 and 0.1 . For the first data set, I was ...
- 11
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2
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35
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Multiple models have extreme differences during evaluation
My dataset has about 100k entries, 6 features, and the label is simple binary classification (about 65% zeros, 35% ones).
When I train my dataset on different models: random forest, decision tree, ...
- 13
1
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2
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409
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Why does using Gradient descent over Stochatic gradient descent improve performance?
Currently, I'm running two types of logistic regression.
logistic regression with SGD
logistic regression with GD
implemented as follows
...
- 479
3
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2
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637
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The central idea behind SGD
Pr. Hinton in his popular course on Coursera refers to the following fact:
Rprop doesn’t really work when we have very large datasets and need to perform mini-batch weights updates. Why it doesn’t ...
- 14.2k
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3
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Why Mini batch gradient descent is faster than gradient descent?
As I understand them:
Mini Batch Gradient Descent :
It takes a specified batch number say 32.
Evaluate loss on 32 examples.
Update weights.
Repeat until every example is complete.
Repeat till a ...
- 709
4
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2
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332
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How is Stochastic Gradient Descent(SGD) used like Mini Batch Gradient Descent(MBGD)?
As I know, Gradient Descent(GD) has three variants which are:
1- Batch Gradient Descent(BGD): processes all the training examples for each iteration of gradient descent.
2- Stochastic Gradient Descent(...
- 1,177
3
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2
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481
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Explanations about ADAM Optimizer algorithm
I'm a beginner in Machine learning and I'm searching for some optimizer for the gradient descent. I've searched many topics about that, and did a state of art of all these optimizers. I have just one ...
