Questions tagged [ann]
The ann tag has no summary.
19 questions
1
vote
1
answer
128
views
Combining standardizing and normalizing my input data for ML gives the best results, why?
When I combine standardizing and normalizing my input data for my hybrid ANN model, it gives the best results.
But I can't find anywhere, why. I based it on a paper's approach but they don't justify ...
- 11
3
votes
1
answer
74
views
Unable to fit ANN to "simple" dataset?
I am really struggling of modeling a dataset that I acquired by doing experiments. Concretely, those are time series (online) data of measurements and the objectives are kinetic parameters that I ...
- 31
2
votes
1
answer
156
views
Why the test accuracy showing some odd behaviour in comparison to train accuracy?
I am currently training an ANN using Sequential(a class from Keras API within tensorflow), and I am optimizing the model's architecture and came across something I have not seen before.
The graph of ...
- 23
0
votes
0
answers
48
views
how do I label my images for computer vision
So I want to do shape recognition task on a flowchart using CNN, but my input images are not labeled and I don't know how to do that automaticaly I mean not manually, anyone can help me please ?
- 1
0
votes
1
answer
63
views
model.evaluate gives low results?
i have an image dataset and there are 6300 images with 5 classes . The features extracted and dataset reduced to 256 features. This dataset gives good results(%99) when tested ANN with Backpropagation(...
1
vote
1
answer
152
views
Does derivative of an activation function refer to process of back-propogation in ANN?
I am confused that in ANN, we use Gradient Descent to find the curve of the optimal points of predicted values.
Let's say we use MSE (Mean Squared Error) and the lost function is 1/2m * (y-y')^2
And ...
- 13
1
vote
1
answer
187
views
How to Improve MLP ANN accuracy
I am trying to improve the accuracy of my model over the UCI Breast Cancer Dataset. There's 426 records, and it is a binary classification model.
...
- 11
0
votes
1
answer
83
views
Encoding Colour Output for a Sequential Neural Network
I’m fairly new to deep learning and AI and my first proper project consists of a model taking 13 or so inputs and one colour output.
Currently, I’ve got 3 outputs (RGB) but I was wondering if I’d be ...
1
vote
1
answer
130
views
Understand the reason of embedding and the size inside it in Pytorch
I'm very new to pytorch - taking a course in udemy.
There is something I find hard to understand and would like to get explaination about, in a bit simpler words than what I can find in the ...
- 299
1
vote
0
answers
76
views
Near duplicate detection algorithms for a near real time system
I'm looking for near-duplicate detection algorithms or techniques for a near-real-time system with large document volumes. I know LSH is the most popular industry-standard algorithm for syntactical ...
1
vote
0
answers
43
views
Some models are over fitting and some are under fitting, please help me where I am doing wrong
I am getting 100% accuracy for the below models. can you please advise me where I am doing wrong? If it is due to overfitting then why other models like below do ...
- 11
1
vote
1
answer
285
views
Combine multiple vector fields for approximate nearest neighbor search
I have multiple vector fields in one collection. My use-case is to find similar sentences in similar contexts. The sentences and contexts are encoded to float vectors. Therefore, I have one vector for ...
- 11
1
vote
1
answer
279
views
Understanding outputs from ANN and how to improve validation loss
I apologise if this is a bit long winded, but it was suggested by another user that I post.
I will start by saying that I am very new to the world of machine learning and deep learning. As such, the ...
- 125
1
vote
1
answer
74
views
MLP sequential fitting
I am fitting a Keras model, using SGD
Input dataset X_train has 55000 entries.
Can anyone explain the yellow highlighted values?
For me, when each epoch is done, this should correspond to 55000/55000....
- 13
1
vote
2
answers
80
views
How can ANN handle varied sized inputs?
I have a dataset with a message (string) and an associated mood. I am trying to use an ANN to predict one of the 6 moods using the encoded inputs.
This is how my X_train looks like:
...
- 141