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Questions tagged [overfitting-underfitting]

143 questions
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Siamese Network-Train own datasets and judged overfitting

I use Siamese Network to train my own dataset.I visualized the training results using Tensorboard.I'm a beginner and I'm not very good at judging if it's an overfit.Please help to see, thank you! Figure 1 and 2 are Train. Figure 3 and 4 are…
Wyuer
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how to prevent overfitting in reinforced learning with vgg16

I'm trying to train a model to recognize facial expressions, so basically a classification problem with 7 classes: img_size=48 batch_size=64 datagen_train=ImageDataGenerator( rotation_range=15, …
Alexander
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How to test for overfitting in regression cross-validation with GridSearchCV?

I am running a regression model of a set of continuous variables and a continuous target. This is my code: def run_RandomForest(xTrain,yTrain,xTest,yTest): cv = RepeatedKFold(n_splits=10, n_repeats=3, random_state=1) # define the pipeline to…
Slowat_Kela
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Good Accuracy, Bad prediction

I am trying to do a multi-class classification project with CNN. My issue is getting good accuracy but not predicting well on validation data. I have introduced l2 regularization but it is not generalizing well. Also tried with different l2 …
Shivani Akotkar
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Class imbalance in CNN model for image classification

I have a dataset with 5 classes, and below there is the number of images in each class: Class1: 6427 Images Class2: 12678 Images Class3: 9936 Images Class 4: 26077 Images Class 5: 1635 Images I run my first CNN model on this dataset and my model was…
amiroruji72
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Despite employing Dropout, MaxPooling, Early Stopping, and Regularizers, my CNN model is still overfitting. How can I further prevent overfitting?

As the title clearly describes the situation I'm experiencing, despite employing Dropout, MaxPooling, EarlyStopping and Regularizers, my CNN model is still overfitting. Also, I've experimented with various learning_rate, dropout_rate, and L1/L2…
talha06
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When to tell if our CNN model is overfitting?

i have this model that i trained with 100 epochs : Model with 100 Epoch and then i save the model and train for another 100 epoch (total 200 epoch): Model with additional 100 epoch (200 epoch) my question is, is my model not overfitting ? is it…
Willy Wijaya
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How to know when an overfitting is taking place?

I have a training data with 3961 different rows and 32 columns I want to fit to a Random Forest and a Gradient Boosting model. While training, I need to fine-tune the hyper-parameters of the models to get the best AUC possible. To do so, I minimize…
Ernesto Lopez Fune
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is it overfitting or data leakage problem?

I have applied Sklearn DecisionTreeClassifier() on a personalized dataset to perform binary classification (class 0 and class 1). Initially classes were not balanced I tried to balance them using : rus = RandomUnderSampler(random_state=42,…
baddy
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Titanic Dataset overfitting: can it be that much?

I am a bit confused as I am training a model that yields circa 88% CV score on the train data while the same model performs poorly on the test data after I submit it ( score of 0.75). This drop of 12 points in accuracy can't be all due to…
sidhom slim
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Can't prevent CNN model from overfitting by reducing layers, increasing Dropout or increasing learning rate

I want to make an image classifier using CNN. There are two types of images in the dataset: men and women. in total there are 2300 images, 20% of which I used for validation. the problem is that my model isn't good at all because of overfitting(I…
bearthum
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Validation loss doesn't decrease (tensorflow)

first of all, sorry for my english, I am facing a problem with my project using tensorflow, i have to code a dictionnary (english-->german), i know it is not easy to figure out where is the problem :/ it is killing me, i am here for any…
R2D2
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When fitting a model with a simple RNN layer, I am hitting a val_accuracy ceiling of exactly 37.62% every time. Why is this happening?

Using the keras simpleRNN layer, I am hitting this wall. I have two other models, one only with fully connected Dense layers, and one using LSTM which work as expected, so I don't think it's the data processing that is the issue. For context, I am…
Stefan Horvath
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Keras CNN instantly overfitting, not dataset issue

Been trying to build a CNN to classify MFCC data, but the model is instantly over-fitting. Data: 18 000 files (80% train, 20% test) 5 labels 5 classes in data are all of equal amounts. This model has been created to handle a lot more files than…
Deividas Brazauskas
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Similar validation accuracy for sparse and non sparse dataset in case of decision trees

The blog https://www.kdnuggets.com/2021/01/sparse-features-machine-learning-models.html mentions that the decision tree overfits the data in the case when we have sparse features. To understand the intuition behind this, I tried fitting a decision…
Deepak Tatyaji Ahire
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