Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.
Questions tagged [supervised-learning]
542 questions
4
votes
1 answer
Addressing synonyms in Supervised Learning for Text Classification
I am using scikit-learn supervised learning method for text classification. I have a training dataset with input text fields and the categories they belong to. I use tf-idf, SVM classifier pipeline for creating the model. The solution works well for…
Shamy
- 379
- 3
- 15
4
votes
2 answers
Creating supervised model in machine learning
I have recently learned how supervised learning works. It learns labeled dataset and predict unlabeled datum.
But, I have a question that is it fine to teach the created model with the predicted datum and then predict unlabeled datum again. And…
hitechnet
- 47
- 3
4
votes
2 answers
Use a different estimator based on value
What I'm trying to do is build a regressor based on a value in a feature.
That is to say, I have some columns where one of them is more important (let's suppose it is gender) (of course it is different from the target value Y).
I want to say:
-…
dark
- 256
- 2
- 12
4
votes
1 answer
Machine learning : find the closest results to a queried vector
I have thousands of vectors of about 20 features each.
Given one query vector, and a set of potential matches, I would like to be able to select the best N matches.
I have spent a couple of days trying out regression (using SVM), training my model…
sebpiq
- 7,540
- 9
- 52
- 69
4
votes
2 answers
Neural network learning fast, false positives
I've recently started implementing a feed-forward neural network and I'm using back-propagation as the learning method. I've been using http://galaxy.agh.edu.pl/~vlsi/AI/backp_t_en/backprop.html as a guide.
However, after just the first epoch, my…
jub
- 213
- 1
- 11
3
votes
0 answers
Pytorch - Training loss not changing with simple CNN model
In an image classification task of around 15 classes, the classes are rathe simple, categorized by color. Not some very high level detail.
The graphs of loss and accuracy over 100 epochs
I am using the below simple CNN model consisting of 2…
AlgoManiac
- 99
- 6
3
votes
2 answers
sklearn: multi-class problem and reporting sensitivity and specificity
I have a three-class problem and I'm able to report precision and recall for each class with the below code:
from sklearn.metrics import classification_report
print(classification_report(y_test, y_pred))
which gives me the precision and recall…
Roz
- 195
- 2
- 10
3
votes
1 answer
What is the difference between args wordNgrams, minn and maxn in fassttext supervised learning?
I'm a little confused after reading Bag of tricks for efficient text classification.
What is the difference between args wordNgrams, minn and maxn
For example, a text classification task and Glove embedding as…
Rajan Raju
- 113
- 7
3
votes
0 answers
Supervised Learning HMM with Pomegranate
thanks for your help, I am new about this topic.
I have a dataset composed of a sequence of binary observable variables associated with a label, like this.
trainset = [ [0,0,1,0],[0,0,1,0],[0,0,0,1],...,]
labels = [ 0,1,2,...,]
states = 3 # number…
i_cook_bit
- 31
- 2
3
votes
1 answer
Making a Prediction from Model Genereted by Decision Tree Algorithm
I've been trying to make a prediction that consists of a DataFrame from the model I've made using the Decision Tree algorithm.
I have got the score for my model, which is 0.96. Then, I have tried to use the model to make a prediction from DataFrame…
ebuzz168
- 1,134
- 2
- 17
- 39
3
votes
1 answer
How to get predicted value in Tensorflow.js
I am trying build predictive system into a MERN app. I am new to Tensorflow and just followed this tutorial which gets relation between Horsepower and Miles per…
Stacy J
- 2,721
- 15
- 58
- 92
3
votes
1 answer
How to add cluster label columns back into original dataframe- python, for supervised learning
I have a column in my data frame which contains Url information. It has 1200+ unique values. I wanted to use text mining to generate features from these values. I have used tfidfvectorizer to generate vectors and then used kmeans to identify…
SSuram
- 61
- 4
3
votes
1 answer
Graph cut performed before training or as a post-processing to a pixel-based classification
I'm currently performing a pixel-based classification of an image using simple supervised classifiers implemented in Scikit-learn. The image is first reshaped into a vector of single pixel intensities, then the training and the classification are…
Hakim
- 3,225
- 5
- 37
- 75
3
votes
1 answer
Tensorflow: Matrix size-incompatible error on Tensors
I am attempting to do binary classification on a univariate numerical dataset with Tensorflow. My dataset contains 6 features/variables including the label with about 90 instances. Here is a preview of my…
luii
- 319
- 3
- 5
- 16
3
votes
1 answer
How to create supervised learning dataset from time series data in python
I have a time series data but there are lots of values for one day as below:
[[day1, x1],
[day1, x2],
[day1, x3],
[day2, x4],
[day2, x5],
[day3, x6],
[day4, x7],
[day4, x8],
[day4, x9],
......]
and so on.
I want to turn this time series…
Ng.Alina
- 59
- 4