Questions tagged [multi-output]
The multi-output tag has no usage guidance.
13
questions
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0answers
19 views
Keras loaded model output is different from the training model output
When I train my model it has a two-dimension output - it is (none, 1) - corresponding to the time series I'm trying to predict. But whenever I load the saved model in order to make predictions, it has ...
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0answers
10 views
Validation Accuracy greater than train accuracy, validation loss lesser than training loss MTL
I am training a multi task model using VGG16.
Datase:
Dataset contain 11K images. There are two tasks:
The dataset is imbalanced,
1) PFR classification: 10 classes
0 --- 5776
10-12 --- 1066
6-...
2
votes
1answer
22 views
Control which features are used for every task in multioutput classification?
I would like to perform a multiclass-multioutput classification task, on vectorized textual data. I started by using a random forest classifier in a multioutput startegy:
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0answers
12 views
What toolbox to use to create multi-output random forest(reggression) with custom spltting function at each node?
I am trying to implement "Real Time Head Pose Estimation fromConsumer Depth Cameras" by Fanelli et al.
I need to train a random forest(regression) with the following criterion
The predicted output is ...
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0answers
27 views
Multi-output and heterogeneous models
What models (including software) support multiple outputs/responses which can have their own loss functions? For example, suppose I would like to fit a model with multiple outputs where one output ...
3
votes
1answer
16 views
Physical modelling with neural networks - single output + stack ensemble vs multi-output
We are trying to replace an existing physical model (8 inputs/7 outputs) with artificial neural networks. The physics behind the existing model is mainly thermodynamics of humid air for air ...
4
votes
2answers
254 views
Are there any Python libraries for predicting the closest value to a correct label out of a variable-size list of possible label values?
Imagine I have the following dataset:
...
2
votes
1answer
34 views
unique predictions for “multi-label multi-output” classification task
Let’s assume that four participants (A, B, C and D) take on five sport-challenges (e.g. swimming, running, ...). Our goal is to predict the placement of each participant for each challenge. Moreover, ...
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16 views
Combining several Multi-Output-Models into a single Multi-Output-Model
I'm trying to create a k-Nearest-Neighbor based model of 76-dimensional input data $I$ and 44-dimensional output data $O$.
Through domain knowledge I know that only certain input dimensions are ...
0
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0answers
14 views
Is it feasable to “predict” 2d (~2x20 array) output using a CNN
I'm trying to generate a "beatmap" (from osu!mania) based on an audio file. To do this, I've applied fast fourier transform (this can change to Mel-frequency cepstrum, but that's not super relevant) ...
0
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1answer
258 views
How to feed data to multi-output Keras model from a single TFRecords file
I know how to feed data to a multi-output Keras model using numpy arrays for the training data. However, I have all my data in a single TFRecords file comprising several feature columns: an image, ...
0
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1answer
37 views
Minimal example: Keras functional API & multi-input/multi-output regression
Problem:
I have a regression problem, where I want to predict two or more numerical outcomes $y_i$ based on a number of numerical features $X_i$. The model would look like: $$y_{1,i}, y_{2,i} = \...
1
vote
2answers
182 views
More output neurons than labels?
When we train a neural network model for a classification problem, we usually have a dense output layer of size equal to the number of labels we have.
If the layer size was greater, the model can ...
