Questions tagged [multi-output]
44 questions
7
votes
2 answers
Custom output names for keras model
I have a model like this with multiple outputs and i want to change it's output names
class MyModel(Model):
def __init__(self):
super(MyModel, self).__init__()
self.layer_one = Dense(1, name='output_name_one')
…
amin msh
- 161
- 2
- 7
5
votes
1 answer
Multi-target regression tree with additional constraint
I have a regression problem where I need to predict three dependent variables ($y$) based on a set of independent variables ($x$):
$$ (y_1,y_2,y_3) = \beta_0 + \beta_1 x_1 + \beta_2 x_2 + \dots + \beta_n x_n +u. $$
To solve this problem, I would…
Peter
- 7,277
- 5
- 18
- 47
4
votes
2 answers
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:
|---------------------|------------------|------------------|
| Feature 1 | Feature 2 | possible labels |
|---------------------|------------------|------------------|
| 1 | …
Guillermo Mosse
- 335
- 1
- 8
3
votes
1 answer
Multi-output, multi-timestep sequence prediction with Keras
I've been searching for about three hours and I can't find an answer to a very simple question.
I have a time series prediction problem. I am trying to use a Keras LSTM model (with a Dense at the end) to predict multiple outputs over multiple…
MGreen
- 31
- 4
3
votes
1 answer
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 conditioning, with some turbomachinery involved, which…
fernikalo
- 31
- 2
2
votes
1 answer
Given a regression based model with many feature variables; what tools would you utilize to figure out which feature variables add the most variance?
Given a hypothetical dataset {S} with 100 X feature variables and 10 predicted Y variables.
X1
...
X100
Y1
....
Y10
1
..
2
3
..
4
4
..
3
2
..
1
Let's say I want to improve the accuracy of Y1. I am prepared to constraint/remove the…
Sad CRUD Developer
- 153
- 5
2
votes
1 answer
What method/algorithm for constrained multi-target regression
I am working with three dimensional measurement data and want to model them using a multivariate linear regression.
I have already implemented a simple gradient descent algorithm to solve the classic regression problem
$y = \beta_0 + \beta_1x_1 +…
schafran
- 131
- 4
2
votes
1 answer
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:
forest = RandomForestClassifier(random_state=1)
multi_target_forest =…
R Sorek
- 53
- 3
2
votes
1 answer
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, let’s assume we have appropriate predictors. We…
Blackout
- 23
- 3
1
vote
1 answer
Multiple output size in neural network
In the paper "A NOVEL FOCAL TVERSKY LOSS FUNCTION WITH IMPROVED ATTENTIONU-NETFOR LESION SEGMENTATION" the author use deep supervision by outputing multiple outputmask which have different scale.
I do not understand how it can work with regards to…
Chopin
- 352
- 2
- 12
1
vote
0 answers
Derivative of multi-output Gaussian Process
I am working on a project where I estimate transition and measurements models for a kalman filter using Gaussian Processes.
In order to linearize the models I require the Jacobian of the estimated Guassian Process.
For the single-output case this…
Michael
- 21
- 4
1
vote
1 answer
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 a three-dimensional output - (none, 40, 1) -…
Marlon Teixeira
- 111
- 2
1
vote
0 answers
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
6-9 --- 1027
4-5 --- 680
1-3 --- 518
30-40 --- 471
20-25…
Obiii
- 131
- 4
1
vote
0 answers
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 multivariate(yaw,pitch).
The input features is…
user27665
- 121
- 3
1
vote
2 answers
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, which is used as input to the Keras model, plus a…
magomar
- 131
- 1
- 5