All Questions
Tagged with neural-network classification
25 questions
12
votes
1
answer
5k
views
Using a pre trained CNN classifier and apply it on a different image dataset
How would you optimize a pre-trained neural network to apply it to a separate problem? Would you just add more layers to the pre-trained model and test it on your ...
- 677
3
votes
1
answer
657
views
When should I oversample data?
I am dealing with multi-class classifiers. My data is unbalanced. Hence, I need to apply sampling techniques before training (undersampling or oversampling). When I apply undersampling, ...
- 151
2
votes
2
answers
2k
views
Explain Binary Classification with output 0.5 (True)
What is the interpretation of output 0.5 of a typical classifier?
I made a prediction and the probability of that data point being from the True class is 0.5.
- 339
7
votes
3
answers
11k
views
Neural network for Multiple integer output
I have a data set that contains 135 input features and 132 output values to be predicted. The input features are all numeric floating point values and each output value would be an integer between [0,...
- 73
4
votes
1
answer
386
views
Fine-tuning a CNN for recognizing two classes, but also being able to tell if none of them is present in an image
I need to fine-tune a CNN to classify two classes: dogs and cats, for example. However, I want the CNN to be able to tell if ...
- 41
3
votes
1
answer
407
views
ANN on Pattern Recognition
I have been trying to apply a simple neural network using keras to predict a sequence of numbers and the rule is if the input integer is odd it should be 4 and if its even it should be 2. Yet the ...
- 33
1
vote
1
answer
129
views
How to analyze repeated measure data for prediction?
In my work, we collect sales data of our products. We have a set of 1st level customers (lets call that group as jacks) with whom we do we business. These jacks then sell our products to end customers ...
- 2,655
0
votes
1
answer
586
views
How to compare models and which settings to keep constant? [closed]
I already posted this in another forum but no response. So, posting it here.
Currently, in clinical practice, clinicians use a score (as a single feature) to predict the mortality of a patient. Now in ...
- 2,655
8
votes
1
answer
4k
views
Class weighting during validation in Keras
I would like to know if the class weighting is also used in evaluating the loss in the validation data during the training. If not, is there a way to adjust the fit() function so that it takes into ...
- 326
7
votes
2
answers
12k
views
Encoding before vs after train test split?
Am new to ML and working on a dataset with lot of categorical variables with high cardinality.
I observed that in lot of tutorials for encoding like here, the encoding is applied after the train and ...
- 2,655
4
votes
1
answer
197
views
How can we scale up the number of classes for deep learning after training a model?
I have trained a deep learning model for a face recognition application. The model has been trained on the existing subjects (or call it classes) in the gallery. Now consider the real world problem, ...
- 106
4
votes
2
answers
4k
views
Is it possible using tensorflow to create a neural network that maps a certain input to a certain output?
I am currently playing with tensorflow, but can't seem to get a hold whether it usefull for my problem?
I need to create a neural network, that is capable of mapping input to output.
The way things ...
- 153
3
votes
1
answer
923
views
Using deep-learning on graph data for binary classification
The data:
I have certain data that I decided to represent it as a graph (I thought it would suit).
So I have the weighted graph data that includes a numeric attribute for each node. (networkx graphs)....
3
votes
4
answers
6k
views
How to deal with class imbalance in a neural network?
Suppose we have a game and its action space contains two possible actions: A and B.
We have a labelled dataset of state-action ...
- 171
3
votes
1
answer
2k
views
Cost sensitive classification with individual cost
I'm currently sitting on a problem, where i'm uncertain if there is not a much simpler solution.
I'm trying to train a DNN with a dataset for a classification task that should be cost sensitive. ...
- 41
3
votes
2
answers
2k
views
Using neural network for "features matching" binary classification
We have a dataset of numerical features from two images and we want to check if these images match or not using only these features.
Basically we have have these columns:
fA1, fA2, ..., fA14: 14 ...
3
votes
1
answer
3k
views
Should estimated probabilities from multi class classification sum to 1
I am using a neural network with sigmoid activation function $h(z) = 1 / {(1+e^{-z})} $ in order to classify image data into 6 categories. When running the trained neural network over new image data, ...
- 133
2
votes
2
answers
2k
views
Neural Network: Backpropagation Works on MNIST, but Training/Test Set Accuracy Very Low
I am building a neural network to learn to recognize handwritten digits from MNIST. I have confirmed that backpropagation calculates the gradients perfectly (gradient checking gives error < 10 ^ -...
- 31
2
votes
3
answers
10k
views
How to combine two different embeddings in the best way possible?
I have two models which are giving two books embedding
Ml_model_a => book1_embedding [ 1, 200 ]
Ml_model_b => book2_embedding [ 1, 200 ]
I am building a ...
- 425
2
votes
1
answer
1k
views
How to perform model selection for One-Class Classification?
Consistency based model selection does not perform well for many datasets for One-Class Classification (OCC). So I am looking for some other model selection criteria.
Since, only one class of data (...
- 311
2
votes
1
answer
938
views
Binary classification model with time series as variables
This is probably a simple question. Assume I'm interested in modelling a binary variable, with various covariates, including ones that are time series observations. In the usual modelling approach, ...
- 236
1
vote
2
answers
7k
views
High-level features of a neural network
I understand how to build and train a neural network like shown below, as well as those low-level features/filters. I wonder what are those high-level features: how exactly do you obtain them from a ...
- 194
0
votes
1
answer
144
views
Is it possible to use Recurrent NN (LSTM) for classification?
I have a dataset C of 50,000 (binary) samples each of 128 features. The class label is also binary either 1 or -1. For instance, a sample would look like this [1,0,0,0,1,0, .... , 0,1] [-1]. My goal ...
- 11
0
votes
1
answer
3k
views
Accuracy keep changing by changing randomState of classifier
I try to classify car sound samples. Using MLPClassifier from Scikit. I'm getting very different and confusing test results between 2 different test sets, and I am stuck:
Training is done with the ...
- 195
0
votes
1
answer
58
views
When to use best hyperparameters - Feature selection or Model building?
I am working on a binary classification with 977 rows using different algorithms
I am planning to select important features using wrapper methods.
As you might know, wrapper methods involve use of ML ...
- 2,655