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Questions tagged [semisupervised-learning]

29 questions
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index 1 is out of bounds for axis 0 with size 1 in machine learning

I don't know why but its showing index 1 is out of bounds for axis 0 with size 1 on acc[i], Its a program for semi supervised learning. Can someone help me what no should be in np.empty() nc =np.arange(.40, 1, .03) acc = np.empty(1) i = 0 for k in…
David Rimo
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why accuracy of my code is not improving even after 10000 iterations?

I am doing a binary classification for 2 classes (0,1), and I generated some 2d random points using make_blobs for semisupervised learning. it is an optimization problem and I want to use GradientDescent to minimize my cost function. but whenever I…
Atefeh Hedayati
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forcasting anomaly in products

I have a question about the forecasting of anomalies. I would be very grateful if you could refer me to some papers that deal with this kind of problem or give me some hints to start with this problem. I have some products that go to a bigger…
Hana
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What are the disadvantages of self-supervised learning in ML?

Self-supervised learning has been on the rise over the past few years. Compared to other learning methods such as supervised and semi-supervised, it does have an edge since it does not require labeled data. I would like to know if self-supervised…
Tony Jesuthasan
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Google Colab RAM issue with semi-supervised CNN model training

I'm trying to training a binary classifier by transfer learning on EfficientNet. Since I have lots of unlabeled data, I use semi-supervised method to generate multiple "pseudo labeled" data before the model go through each epoch. Since Colab has its…
Vic
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Probelm in semi-supervised learning of CNN

I conducted semi-supervised learning to label the unlabelled image in dataset. By utilizing the unlabelled image as input, the CNN model will product a probs index after softmax calculation. If the value over certain number(0.65 for example), I will…
Xi Wang
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How to perform positive unlabeled learning using a binary classifier?

I have setup a bagging classifier in pyspark, in which a binary classifier trains on the positive samples and an equal number of randomly sampled unlabeled samples (given scores of 1 for positive and 0 for the unlabeled). The model then predicts the…
LN3
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TypeError: Fetch argument 0 has invalid type , must be a string or Tensor

I'm trying to add custom metrics (precision, recall and f1) to my run using the TKipf GCN model https://github.com/tkipf/gcn. I built up masked functions for those metrics, and when I tried integrating them into the tf.session.run call in the…
KareemAlaa2001
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how to change the labels in a datafolder of pytorch?

I first load an unlabeled dataset as following: unlabeled_set = DatasetFolder("food-11/training/unlabeled", loader=lambda x: Image.open(x), extensions="jpg", transform=train_tfm) and now since I'm trying to conduct semi-supervised learning: I'm…
李彥儒
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Text classification for unlabeled data

I want to classify data into two classes based on parameters given. My data is publications from two different sources and I want to classify it into "match" or "non-match"; when comparing the dataset1 with dataset2. The datasets are unlabeled text…
Ocean
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Indices of cluster for labelling to perform semi supervised learning

I have fitted a k-means algorithm on 5000+ samples after converting to vector after using tfidf. I want to label 5 nearest points from the 15 clusters formed.I have the labels on a different dataframe, but do not want to use them completely.How to I…
Shraddha S
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I want to train a Variational Autoencoder with both labeled samples and unlabeled samples

The images are like this: fake image generated with no label real image with label I have 12000 fake images, that I generated based on bright spots on an image with no label. I have 1200 real images, that have annotations and true labels. I want the…
Savoyevatel
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Nearest Neigborood using a confidence region

I have more than 1M data points and 32 of them (Orange in the pic) are my true class. I would like to find similar blue points to the orange ones. Feature vectors are just embeddings. The approach that I took is to build a pseudo 95 confidence…
3nomis
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