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Questions tagged [overfitting-underfitting]

143 questions
18
votes
2 answers

What is C parameter in sklearn Logistic Regression?

What is the meaning of C parameter in sklearn.linear_model.LogisticRegression? How does it affect the decision boundary? Do high values of C make the decision boundary non-linear? How does overfitting look like for logistic regression if we…
Abdulwahab Almestekawy
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1 answer

Overfitting when fine-tuning BERT sentiment analysis

I am newbie to Machine Learning in general. I am currently trying to follow a tutorial on sentiment analysis using BERT and Transformers https://curiousily.com/posts/sentiment-analysis-with-bert-and-hugging-face-using-pytorch-and-python/ However…
hhp
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PolynomialFeatures and LinearRegression returns undesirable coefficients

import os import pandas as pd import matplotlib.pyplot as plt from sklearn.pipeline import Pipeline from sklearn.linear_model import LinearRegression from sklearn.preprocessing import PolynomialFeatures csv_path = os.path.join('',…
good_evening
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Why is my basic CNN model NOT overfitting segmentation image dataset?

I have a dataset of 2000x256x256x3 RGB images (of pink tissue containing purple/blue nuclei) and corresponding ground truth of size 200x256x256x1. The ground truth images are binary. Now, here is my model (Tensorflow version 1.x and Keras): def…
prc777
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3
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1 answer

LSTM for 30 classes, badly overfitting, cannot go over 76% test accuracy

How to classify job descriptions into their respective industries? I'm trying to classify text using LSTM, in particular converting job description Into industry categories, unfortunately the things I've tried so far Have only resulted in 76%…
Harsh gupta
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2
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0 answers

How to correct overfitting (by placing dropout layers) in tensorflow image segmentation model?

I followed Tensorflow's tutorial here to create a custom image segmentation model. My model looks like the following, and is trying to create masks like these: However, I am having over-fitting problems so I would like to introduce some Dropout…
firsttry
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2
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1 answer

how check overfitting on point pattern on a linear network using spatstat

I have been using lppm (point pattern on a linear network) on spatstat with bunch of covariates and fitting a log-linear model but I couldn't see how to check over-fitting. Is there a quick way to do it?
iHermes
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Which value should I choose as standard deviation for Gaussian Noise in my data?

I am adding Gaussian Noise using the Keras GaussianNoise layer to my data to corrupt it to prevent overfitting. I have analysed my data and the mean of all values is 7624 and the standard deviation is 2591. I have attached a picture of the…
Harsh Motwani
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2
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1 answer

Is there a loss function considering bias and variance?

I'm trying to understand the bias and variance more. I'm wondering if there is a loss function considering bias and variance. As far as I know, the high bias makes underfit, and the high variance makes overfit. the image from here If we can…
tucan9389
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1 answer

CatBoost: Are we overfitting?

Our team is currently using CatBoost to develop credit scoring models, and our current process is to... Sort the data chronologically for out-of-time sampling, and split it into train, valid, and test sets Perform feature engineering Perform…
swritchie
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1 answer

How do I understand whether yolov4 training is overfitting?

I'm training to make human detection with YOLOv4 in the custom dataset. I used this command to train the dataset: !./darknet detector train data/obj.data cfg/custom-yolov4-detector.cfg yolov4.conv.137 -dont_show -map At the end of the training, it…
John Amell
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1
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0 answers

Cannot reduce overfitting on BERT+BiGRU+Softmax network for named entity recognition

I am currently attempting to build a named entity recognition system for the Moroccan Dialect using BERT+ BiGRU+Softmax architecture. I am encountering overfitting (F1 score on validation set around 78% and F1 score on training set around 98%). I am…
hananour
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when using Dice loss, should the predections be probabilites like [0.3,0.7] or I should set threshold to make them either 0 or 1 like [0,1] (trsh=0.5)

I'm using Unet model and diceloss for binary segmentation with 1 channel. I'm really confused if I should give the dice loss the predections as they are (after applying sigmoid) or I have to set threshold before passing it to the loss function I…
abdelmadjid tahar
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1 answer

How to avoid overfitting on multiclass classification OvR Xgboost model / class_weight in Python?

I try to build multiclass classification model in Python using XGBoost OvR (OneVsRest) like below: from xgboost import XGBClassifier from sklearn.multiclass import OneVsRestClassifier from sklearn.metrics import roc_auc_score X_train, X_test,…
dingaro
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Implementing regularization Pytorch vs Keras

Do you know what would be the analog of doing something like this in Keras? alpha = 5 pearson_corr = correlation.calculate_correlation(train) pearson_index = [x for x in range(len(pearson_corr)) if abs(pearson_corr[x])<0.3] self.corr_l1_penalty =…
Caterina
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