Questions tagged [multi-output]
The multi-output tag has no usage guidance.
44
questions
1
vote
0
answers
14
views
Can the k-index in either of the two individual locations be used to predict the estimated kp-index?
The k-index measures the condition of the magnetosphere. It is usually averaged over three hour, so each day has 8 measurements.
The planetary k-index (kp-index) is an average of the measures taken ...
- 173
1
vote
0
answers
23
views
Validation Accuracy incorrect when multiple outputs are in the dense layer!
I have a set-up a parallel LSTM architecture with two LSTM layers and one Dense layer producing several outputs which are converted into a probability with a sigmoid function on the dense layer. For ...
- 11
0
votes
0
answers
15
views
Is it possible to train an ML model that predicts two different types of variables (numeric, categorial)? Is learning a ranking function possible?
Problem setup:
We are given a set of training instances and an algorithm C, composed of two randomized algorithms, A and B. Algorithm A has no hyperparameters. In contrast, B has only one ...
0
votes
0
answers
16
views
How do I get ktrain to return a multilabel output in tabular regression?
So the output vector I'm training a ktrain model on is 2 dimensional (the outputs are ['Temp', 'Velo']. And ktrain is even able to compute these when I use predictor.predict (see attached image), but ...
- 1
0
votes
0
answers
47
views
Predict length and width of an object (NLP/Tabular Data)
I need to do a model that predict the dimensions (length and width) of an object, given some inputs. The input are not important for my question, but are not images.
Should I just do a double ...
- 323
0
votes
0
answers
47
views
Feature generation for multi-label classification
Problem statement
Predict customer's likelihood/propensity to buy multiple category of products from a grocery store give past purchase data (Given a set of users at time 𝑡, predict whether they will ...
- 123
0
votes
1
answer
38
views
using forecast values from a univariate model as Input to linear regression?
I have weekly time series data for the last 2 years with variables "week", "marketing_spend", "web_traffic", and "revenue" ...
- 101
0
votes
0
answers
31
views
Multi output regression model with non categorical text data
I am doing a multioutput regression model where 1 input and 6 output. My dataset contain all non categorical text data. I used countvectorization in the preprocessing but got an error while fitting ...
0
votes
0
answers
43
views
Sampling strategies in multi-target classification
I am dealing with multi-target binary classifications (I have two targets). I need to use a sampling strategy. I have tried imblearn.pipeline but I'm getting the same error as this time when I'm ...
- 101
0
votes
0
answers
25
views
lstm multi-step
i have a question about multi step forecasting result. for example, i have a dataset from 1 to 100. I applied sliding window technique and i used 24 timesteps to predict 20 future data. i had ...
- 1
0
votes
0
answers
20
views
Varying output size in recurrent neural network
My dataset has an varying size in the output data (meaning can be a vector of 2 or 5 integers). I read that recurrent neural network (RNN) can be a solution to that but did not find an easy example of ...
- 11
1
vote
0
answers
200
views
How do I build a multi-input and multi-output neural network?
I want to build a neural network classifier which has as inputs array of dimension (24, 2, 20001) and as outputs array of dimension ...
0
votes
1
answer
484
views
Grid-search for a multi-output regression task using Scikit-learn's API
I'm trying to make a model for a multi-output regression task where $y=(y_1, y_2,..., y_n)$ is a vector rather than a single scalar. I am using Scikit-learn's ...
- 115
0
votes
1
answer
18
views
After validating a model, how to extract optimal inputs inputs based on a given output?
I Looked around and could not find a similar question (at least not with the keywords I used).
After I trained and tested a classification model, I understand how I can supply it with a new input to ...
- 1
0
votes
1
answer
70
views
Can ML or DL Predict output vector target?
I have output data as follows:
Then I encode into :
Then I convert into vector:
The input of model is word embedding of sentence.
My question is that: Can ML or DL return a vector output above? If ...
- 21
0
votes
1
answer
651
views
Why do we need "MultiOutputClassifier" if we can get same results without it?
I am learning about multi-label multi-classification examples
It is when you have a case like this
...
- 539
-1
votes
1
answer
128
views
How to show combined overall accuracy for a multi-ouput model in Keras?
I have a model of the following structure. It has 6 outputs. Given an image, the model predicts classes of 6 different components from the image.
The metrics I used are:
As you can see it outputs an ...
- 1
0
votes
1
answer
21
views
Output representation for a neural network to learn grid-based game with multiple units
I have a round based game played on a grid map with multiple units that I would like to control in some fashion using neural network (NN). All of the units are moved at once. Each unit can move in any ...
- 101
1
vote
1
answer
1k
views
How to calculate a single accuracy for a model with multiple outputs in Keras?
Consider the following, rather simple, model:
...
- 277
0
votes
1
answer
322
views
Early stopping based on average val_loss of last ten epoches and with some n partiences
I am training a DNN with CNN in Keras. Though, I can write an EarlyStopping criteria based on val_loss but due to minor oscillations in the val_loss, I want to monitor the average validation loss over ...
1
vote
0
answers
26
views
Would it make sense to have an output layer connected to other output layers in a NN?
I'm working with data that has multiple variables which could be predicted, nonetheless I need to predict just one that is directly correlated to all of the others. Would it make sense to have a NN ...
0
votes
0
answers
46
views
Multi-Label Regression of Categorical Probability Distribution that adds up to one
What would an ideal Tensorflow/Keras architecture look like, if the target is a multi-regression with values that add up to one?
Toy Example: Tv Channels
You work for a big TV-Station and your boss ...
- 101
5
votes
1
answer
564
views
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 + \...
- 7,366
0
votes
1
answer
66
views
Multiple targets in a classification problem
I have a vector of length $n \gt 4$ which has exactly 4 targets, so for example [0, 0, 0, 1, 0, 1, 0, 1, 1]. I would like to know how I can modify the softmax ...
- 1
0
votes
1
answer
32
views
3
votes
1
answer
1k
views
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) ...
- 31
2
votes
1
answer
36
views
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 ...
2
votes
1
answer
144
views
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 ...
- 131
0
votes
1
answer
60
views
How To Motivate A Neural Network
Suppose a training dataset contains the following inputs:
company size
number of employees
turnover
average salary
country
years of operation
...and outputs:
...
- 111
0
votes
1
answer
483
views
Neural Network for Multiple Dependent Outputs
I have a dataset with approx 6 input features and 5 output values to be predicted. I am trying to understand what kind of neural network would be most suitable to assign probability across multiple ...
- 111
1
vote
1
answer
398
views
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 ...
- 352
7
votes
2
answers
4k
views
Custom output names for keras model
I have a model like this with multiple outputs and i want to change it's output names
...
- 161
1
vote
0
answers
37
views
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 ...
- 21
1
vote
1
answer
343
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 ...
- 111
1
vote
0
answers
121
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-...
- 131
2
votes
1
answer
54
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:
...
- 53
1
vote
0
answers
26
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 ...
- 121
3
votes
1
answer
140
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 ...
- 31
4
votes
2
answers
357
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:
...
- 335
2
votes
1
answer
124
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, ...
- 23
0
votes
0
answers
75
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 ...
- 1
1
vote
2
answers
5k
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, ...
- 131
0
votes
1
answer
670
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} = \...
- 7,366
1
vote
2
answers
545
views
A neural network with more output neurons than labels
When we train a neural network model for a classification problem, we usually have a dense output layer of a size equal to the number of labels (classes) we have.
If the layer size was greater, the ...
- 221