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- W4225303525 abstract "Regression is one of the most used techniques in the machine learning domain, so it is very important to have high accuracies in the model. There is a standard machine learning approach to the build model. The basic machine learning pipeline does not perform efficiently in terms of accuracies. In this paper, we will propose a slightly enhanced version of the basic machine learning pipeline which helps attain better model performance. The proposed algorithm works on the principle of retraining the model. The predictions of the first training process are used to train the model a second time. The proposed approach was seen to have improved the accuracies by one to seven percent. We have tested the proposed approach over six algorithms on a traffic prediction dataset." @default.
- W4225303525 created "2022-05-05" @default.
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- W4225303525 date "2022-03-23" @default.
- W4225303525 modified "2023-09-27" @default.
- W4225303525 title "An Approach to Reduce Error in Regression Problems with an Implementation" @default.
- W4225303525 doi "https://doi.org/10.23919/indiacom54597.2022.9763163" @default.
- W4225303525 hasPublicationYear "2022" @default.
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