All Questions
Tagged with machine-learning regression
1,230 questions
0
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19
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Get analytical equation of RF regressor model [duplicate]
I have the following dataset:
X1 X2 X3 y
0 0.548814 0.715189 0.602763 0.264556
1 0.544883 0.423655 0.645894 0.774234
2 0.437587 0.891773 0.963663 0.456150
3 ...
- 4,492
0
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2
answers
90
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Regression fails with poor initial guess [closed]
Consider a regression task where the parameters of the model differ significantly in magnitude, say:
def func(x, p):
p1, p2, p3 = p
return np.sin(p1*x) * np.exp(p2*x) * p3
# True Parameters:
...
- 11
1
vote
1
answer
54
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Do Evaluate process in Palantir Foundry Model Training parameters (mean, sd) from "Train data" to "Test data"?
If I understand the process correctly, when scaling test data in machine learning, you should use the scaling parameters (like mean and standard deviation) learned from the training data to transform ...
- 11
0
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0
answers
39
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Tweedie Regression: power >=2 ' "Some value(s) of y are out of the valid range of the loss", but y values are not
I'm running a Tweedie Regression, and for powers >= 2, I get an error telling me that my y values are out of the range of the HalfTweedieLoss. I understand the valid range of y for this loss to be &...
3
votes
1
answer
54
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Error in predict.train .... type must be either "raw" or "prob"
I am using caret with ranger for regression but I need to set quantreg = TRUE as I need this to compute quantiles (see below) some extract of my code. But I am getting this error:
Error in predict....
- 33
1
vote
0
answers
43
views
Error while running BayesSearchCV for finding best hyperparameter of ANN regression
I try to apply deep learning to make regression (6 independent variables and 1 dependent variable).
Similar problems but has not been solved:
Error while running Bayesian for finding best ...
0
votes
0
answers
27
views
Error while running Bayesian for finding best hyperparameter
I try to apply deep learning to make regression (6 independent variables and 1 dependent variable)
I am trying to use Bayesian optimisation to find the best parameter for ANN regression (artificial ...
0
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0
answers
35
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Techniques for adaptive prediction with feedback in an evolving feature space
I am working on a prediction problem where the target variable 𝑦 is drawn from a normal distribution, and the relationship between the continuous feature space 𝑋 and 𝑦 remains stable over time. ...
- 3,768
0
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0
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27
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the problem with learning the LSTM neural network
I need to create a model that will predict the error of some signal in time, i.e. solving the time series regression problem. I use LSTM for this:
class MyLSTM(nn.Module):
def __init__(self, ...
- 1
0
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0
answers
64
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Training Kernel Ridge Regression with subsets of features contributing to the final target
I'm working on a machine learning problem using Kernel Ridge Regression (KRR) in Python with scikit-learn. My goal is to train a kernel where subsets of features contribute to the target prediction.
...
- 11
-2
votes
1
answer
46
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How to speed up training of Random Forest Regression and SVR?
I am trying to create a regression model to predict the closing price of bitcoin using the folloςing dataset: https://www.kaggle.com/datasets/prasoonkottarathil/btcinusd/data?select=BTC-2021min.csv
...
-1
votes
1
answer
73
views
Getting ValueError: All arrays must be of the same length
I have been trying to convert a dictionary into a dataframe but everytime i keep getting ValueError: All arrays must be of the same length. i Have checkde the length of each array and confirmed them ...
- 1
0
votes
0
answers
33
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Unexpected MSE Behavior in Online Federated Learning Simulation Using Random Fourier Features (RFF) Based Kernel LMS
I am trying to simulate the Online Federated Learning framework presented in the paper "Communication-Efficient Online Federated Learning Framework for Nonlinear Regression" by Gogineni et ...
0
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0
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33
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Multi Output Regression to predict cost and revenue from ROAS and other features
I am trying to predict expected Cost and Revenue for hotel_name and Channel from user inputs: ROAS (Revenue / Cost), hotel_name, and month. I've attempted using Multioutput Regression and the pymc-...
- 473
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0
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62
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LSTM as regressor in Double Machine Learning
I want to use Double Machine Learning (DML) to do some causality studies. For this I am using the DoubleMLIRM from the doubleml package. The DML uses two ML/DL/NN approaches; one for regression and ...
- 398