Questions tagged [svr]

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Get negative predicted value in Support Vector Regresion (SVR)

I am doing Covid-19 cases prediction using SVR, and getting negative values, while there should be no number of Covid-9 cases negative. Feature input that I was used is mobility factor (where have ...
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Functional form for machine learning models

I am new to the field of machine learning and I have a question. Is there a way to print the function of any machine learning model, just like Y=mX + C (equation for straight line). For eg. support ...
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180 views

Why do I get an ValueError for an SVR model with RFE, but only when using pipeline?

I am running five different regression models to find the best predicting model for one variable. I am using a Leave-One-Out approach and using RFE to find the best predicting features. Four of the ...
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compare SVR with medium regression

We usually compare Supporting vector regression (SVR): $$\mathcal{L} = C\sum\limits_{n=1}^{N}\Big(|y_i - g(x_i)| - \epsilon\Big)^+ + \dfrac{1}{2}||w||^2.$$ and ridge regression (RR): $$\mathcal{L} = \...
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Support Vector Regression for Time-Series Model

As the title is clear, I would like to know it is possible to use SVR (Support Vector Regression) algorithm for Time-series problems?
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230 views

Trouble performing feature selection using boruta and support vector regression

I was trying to select the most important features of a data set using Boruta in python. I have split the data into training and test set. Then I used SVM regressor to fit the data. Then I used Boruta ...
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1 answer
62 views

How important is outcome variable scaling in SVM regression?

Should I scale outcome variable for SVM regression? What is the magnitude of impact of outcome variable scaling in SVM regression?
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266 views

SVR - RMSE is much worse after normalizing the data

I'm building a model using a custom kernel SVR that looks into a few of my dataframe's features and checks the proximity/distance between each pair of datapoints. The features are weigthed and the ...
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-1 votes
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6k views

NotFittedError says this StandardScaler instance is not fitted yet while using inverse_transform() [closed]

I have a dataset and i have used Support Vector Regression.So i needed to use StandardScaler module from sklearn.preprocessing fro Feature Scaling. After training my model when i came to predict it ...
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1 answer
1k views

Scalling and unscalling of data for SVR prediction

I'm trying to use SVR to predict a certain feature. I create the model with the following code: ...
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2 answers
981 views

Which performs better in time series forecasting, LSTM or SVR?

I have run LSTM and SVR models on various datasets having sample values in the range of 1-4000 and the MAPE obtained in SVR was consistently lesser than that obtained through LSTM. I was told the ...
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118 views

Combine AdaBoost and Support Vector Regression?

I have read several papers about using SVM instead of decision tree in AdaBoost, but I haven't seen any papers about using support vector regression (SVR) in AdaBoost. However, if using support vector ...
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3 votes
1 answer
2k views

SVR is giving same prediction for all features

I'm creating a basic application to predict the 'Closing' value of a stock for day n+1, given features of stock n using Python and Scikit-learn A sample row in my dataframe looks like this (2000 rows) ...
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1 vote
0 answers
64 views

Understanding Support Verctor Regression (SVR)

This question also asked on another StackExchange with Bounty. Question here. I'm working with SVR, and using this resource. Erverything is super clear, with epsilon intensive loss function (from ...
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2 votes
1 answer
87 views

How we can have RF-QLearning or SVR-QLearning (Combine these algorithm with a Q-Learning )

How we can have RF-QLearning or SVR-QLearning (Combine these algorithm with a Q-Learning )? I want to replace the DNN section of Qlearning with a RF or SVR but the problem is that there is no clear ...
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1 vote
0 answers
55 views

spatiotemporal prediction using support vector regression

i am using a geographic dataset and i intend to use SVR as machine learning method for predicting spatiotemporal patterns from this dataset. My question is does SVR canensure spatiotemporal ...
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3 votes
1 answer
2k views

Should the output of regression models, like SVR, be normalized?

I have a regression problem which I solved using SVR. Accidentally, I normalized my output along with the inputs by removing the mean and dividing by standard ...
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