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Data Science

Questions tagged [semi-supervised-learning]

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29 questions
Info Newest Frequent Votes Active Unanswered
0
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2answers
21 views

What kind of learning in this training situation when anomaly detection? Supervised learning,semi-supervised learning or unsupervised learning?

I am doing anomaly detection recently, one of the methods is using AEs model to learn the pattern of normal samples. Determine it as an abnormal sample if it doesn’t match the pattern of normal ...
0
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0answers
10 views

what is clamping in label propagation

I'm not clear about what the clamping does in label propagation. I checked the document in scikit learn. label propagation What does it meany by change the weight of the true ground labeled data ...
0
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0answers
29 views

How to deal with small amount of labeled samples?

I'm trying to develop skill to deal with very small amount of labeled samples (250 labeled/20000 total, 200 features) practicing on Kaggle "Don't Overfit" dataset (Traget_Practice have provided all 20,...
0
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1answer
25 views

What is the convergence criteria of a semi-supervised learning algorithm?

I would like to know when to stop doing semi supervision? For example, if I learn a classifier from a small dataset and then use it to label a pool of unlabelled dataset. I then use the newly labelled ...
1
vote
1answer
24 views

Accuracy after selftraining didn't change

I used Decisiton Tree Classifier which I trained with 50 000 samples. I have also set with unlabeled samples, so I decided to use self training algorithm. Unlabeled set has 10 000 samples. I would ...
0
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1answer
26 views

How to get probability of classification

I have binary classification, I tried several model KNN, SVM, decision tree and random forest. I have 50 000 samples, X_train has 50 000 rows and 2300 columns. ...
1
vote
0answers
9 views

General way of constructing adjacency matrix in Laplacian SVM semi-supervised technique

I am trying to implement a Laplacian SVM classifier (trained in primal) using algorithm from this paper. I would like to know what is the most common way of constructing adjacency matrix and the most ...
2
votes
0answers
13 views

Neural Network for detecting/checking for requirements in diagrams

My question is more about what approach is a good/the best approach for my problem: THE PROBLEM - I'm an (mechanical/software) engineer and we take extensive amount of time to review technical ...
1
vote
0answers
43 views

Improving automated ingestion system using Machine Learning and/or NLP

I'm working on a automated ingestion system which takes a PDF or doc file or a URL. It then parses the file and get me the required text in a json format but there are some error and there are few ...
0
votes
1answer
27 views

Adapting Neural Network to new domain without labels

Is there an approach for the following problem: Lets say, I trained a neural network on a big dataset for categorizing different fruits in $k$ classes. Afterwards I got a nice model, which performs ...
0
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0answers
37 views

Semi-supervised learning for regression

It is mentioned on this page that Label Propagation of scikit-learn can be used for regression also. However, nothing is ...
0
votes
1answer
57 views

how to build a predictive model without training data neither historical data

I m trying to score "how much a product is expected in the market". I created some features: How much this product is used each year. Where was it used . how many product for each country. the main ...
2
votes
1answer
287 views

Semi Supervised Learning without label propagation

I am trying to cluster some words by affinity. Using Word2Vec I obtained vector representation of every word that I can cluster with a normal unsupervised method. Of these words, though, I know the ...
1
vote
0answers
26 views

Why should each layer's child network output be close to parent network's output for variance regularizer?

I am reading up on PEA (Pseudo ensemble agreement) regularizer. specificaly in the neural networks domain. It introduces the concept of perturbing the model a little and forcing the model to make ...
1
vote
0answers
37 views

Semi-supervised Learning doubt

I'm reading "Hands on machine learning" by Aurelien Geron. He stated that semi-supervised learning is: Some photo-hosting services, such as Google Photos, are good examples of this. Once you ...
2
votes
2answers
123 views

Time series binary classificaiton with labelling issues

My situation is quite complicated so I will give a similar example from a simpler domain. Suppose we want to try to predict WHEN a mobile game users will make a purchase if given a sale. Almost every ...
0
votes
1answer
190 views

suggest ingredients based on recipe title [closed]

I would like to construct system that would suggest user ingredients once he/she inputs title of the recipe. I think that this is the task of machine learning or AI, but on the other hand I am pretty ...
1
vote
1answer
31 views

Problem faced when collect data randomly from cluster [closed]

I have a semi structured data set. I need to collect some data (unlabeled) randomly for labeling. As initiative at first I separated labeled and unlabeled data. Then I convert those data from string ...
-1
votes
1answer
309 views

How to do semi-supervised learning for regression

I am doing regression analysis on a data set with over 20000 samples using scikit learn. Trying to use regression models to fit three features to label which is a score ranges from 0 to 10. Problem is ...
0
votes
1answer
36 views

Can You Purposely Bias A Clustering Model?

We have a large amount (Billions) of high cardinality, mixed nominal & numerical data, and are performing some clustering on it as an experiment. There is a small subset of these data, however, ...
2
votes
1answer
5k views

Custom conditional loss function in Keras

I'm looking for a way to create a conditional loss function that looks like this: there is a vector of labels, say l (l has the same length as the input x), then for a given input (y_true, y_pred, l) ...
4
votes
4answers
3k views

Why positive-unlabeled learning?

Machine learning can be divided into several areas: supervised learning, unsupervised learning, semi-supervised learning, learning to rank, recommendation systems, etc, etc. One such area is PU ...
0
votes
0answers
43 views

Having measurements of a medical instrument how to improve model with demographic data?

There is a medical instrument that produces various measurements. These measurements are being used as inputs to a model to classify the health condition of a patient. The health condition is binary, ...
1
vote
0answers
328 views

How should I construct a binary classifier for thousands of positive data and millions of unlabeled data?

So far, I have stumbled upon many advices and papers on PU Learning and Unary classification. TLDR: Does anyone have suggestions for specific algorithm or implementation for labeled data of only one ...
3
votes
1answer
138 views

Probability for label correctness in semi-supervised learning

I am aware of the existence of semi-supervised learning approaches, such as the Ladder Network, where only a subset of the data is labeled. Are there any methods or papers which consider correctness ...
5
votes
2answers
419 views

General strategy for imbalanced, semi-supervised, sparse problem

I am looking for some general advice on where to start with this problem. There are 350 sparse (low positive integer) features. I have 2000 positives, 1000 negatives, and infinite unlabeled data, ...
5
votes
3answers
137 views

Predictive clustering

I have an hypothesis but i don't know if it's true. If the cluster is dense and we apply a supervised learning on this data, the model generated by this cluster will be more efficient for new data ...
2
votes
1answer
193 views

Generic strategy for object detection

I have a huge collection of objects from which only a tiny fraction are in a class of interest. The collection is initially unlabelled, but labels can be added using an expensive operation (for ...
11
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3answers
2k views

Build a binary classifier with only positive and unlabeled data

I have 2 datasets, one with positive instances of what I would like to detect, and one with unlabeled instances. What methods can I use ? As an example, suppose we want to understand detect spam ...