Questions tagged [test-datasets]

For questions related to test (or testing) datasets in the context of machine learning. A test dataset is any dataset that is not used for training the model but just to evaluate it, in particular, its ability to generalize to unseen data.

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Why does test data need to be labelled? [closed]

I have a problem understanding why test data needs to be labelled to test a trained faster R-CNN model. Maybe it's basic, but I don't get why it needs to be labelled. When an image is not obvious, ...
Alexandru Lebada's user avatar
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How can validation accuracy be more than test accuracy?

I have been trying to implement DenseNet on small dataset using k-fold cross validation. Training accuracy is 94% ,validation accuracy is 73% whereas test accuracy is 90%.I have taken 10% of my total ...
srij's user avatar
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Why does the SVM perform poorly on test data that has a different class distribution than the training data?

Do you know why the SVM performs poorly on test data that has a different class distribution than the training data? The training data has around 15 classes, and the additional testing data has around ...
Allie's user avatar
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2 answers
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Why is the WMT16 dataset favoured for evaluating machine translation models?

The Workshop on Statistical Machine Translation has released translation challenges each year from 2004 on, which feature a dataset of sentence pairs in a variety of languages. Even though the ...
Zwiebak's user avatar
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1 answer
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Given a dataset of people with and without cancer, should I split it into training and test datasets such that the same person is not in both?

I have a database that contains healthy persons and lung cancer patients. I need to design a deep neural network for the binary classification problem (cancer/no cancer). I need to split the dataset ...
Noha's user avatar
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-1 votes
1 answer
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how to decide the optimum model?

I have split the database available into 70% training, 15% validation, and 15% test, using holdout validation. I have trained the model and got the following results: training accuracy 100%, ...
user50778's user avatar
1 vote
1 answer
1k views

What does it mean by overfitting the test set?

Consider the following statement from p14 of Naive Bayes and Sentiment Classification While the use of a devset avoids overfitting the test set, having a fixed training set, devset, and test set ...
hanugm's user avatar
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1 vote
2 answers
350 views

Are the held-out datasets used for testing, validation or both?

I came across a new term "held-out corpora" and I confused regarding its usage in the NLP domain Consider the following three paragraphs from N-gram Language Models #1: held-out corpora as a ...
hanugm's user avatar
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1 answer
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What are possible ways to combat overfitting or improve the test accuracy in my case?

I have asked a question here, and one of the comments suggested that this is a case of severe overfitting. I made a neural network, which uses residual boosting (which is done via a KNN), and I am ...
jr123456jr987654321's user avatar
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Why doesn't U-Net work with images different from the dataset?

I have implemented a U-Net, similar to this implementation, but for a different dataset, this one, to segment roads. It works fine using the test folder images, but, for example, when I pick a print ...
FourZeroFive's user avatar
1 vote
0 answers
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Is there a way, while training (with contrastive learning) the embedding network, to find the test accuracy?

I aim to do action recognition in videos on a private dataset. To compare with the existing state-of-the-art implementations, other guys published their code on Github, like the one here (for the ...
krishna chaitanya's user avatar
1 vote
1 answer
134 views

How to build a test set for a model in industry?

Most of the tutorials only teach us to split the whole dataset into three parts: training set, develop set, and test set. But in the industry, we are kind of doing test-driven development, and what ...
Lerner Zhang's user avatar
3 votes
1 answer
84 views

How do I select the (number of) negative cases, if I'm given a set of positive cases?

We were given a list of labeled data (around 100) of known positive cases, i.e. people that have a certain disease, i.e. all these people are labeled with the same class (disease). We also have a much ...
Otto's user avatar
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1 vote
0 answers
49 views

Wouldn't training the model with this data lead to inaccuracies since the testing data would not be normalized in a similar way?

I was trying to normalize my input data images for feeding to my convolutional neural network and wanted to use standardize my input data. I referred to this post, which says that ...
user33681's user avatar
3 votes
1 answer
3k views

What is the reason behind using a test batch size?

If one examines the SSD: Single Shot MultiBox Detector code from this GitHub repository, it can be seen that, for a testing phase (evaluating network on test data set), there is a parameter ...
carobnodrvo's user avatar
1 vote
1 answer
984 views

How to perform PCA in the validation/test set?

I was using PCA on my whole dataset (and, after that, I would split it into training, validation, and test datasets). However, after a little bit of research, I found out that this is the wrong way to ...
LVoltz's user avatar
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4 votes
1 answer
221 views

What are "development test sets" used for?

This is a theoretical question. I am a newbie to artificial intelligence and machine learning, and the more I read the more I like this. So far, I have been reading about the evaluation of language ...
little_mice's user avatar