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Questions tagged [supervised-learning]

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.

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Is the bias node necessary in very large neural networks?

I understand the role of the bias node in neural nets, and why it is important for shifting the activation function in small networks. My question is this: is the bias still important in very large networks (more specifically, a convolutional neural…
Hungry
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Plot learning curves with caret package and R

I would like to study the optimal tradeoff between bias/variance for model tuning. I'm using caret for R which allows me to plot the performance metric (AUC, accuracy...) against the hyperparameters of the model (mtry, lambda, etc.) and…
Gabriele B
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How do I use principal component analysis in supervised machine learning classification problems?

I have been working through the concepts of principal component analysis in R. I am comfortable with applying PCA to a (say, labeled) dataset and ultimately extracting out the most interesting first few principal components as numeric variables from…
tumultous_rooster
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Retraining an existing machine learning model with new data

I have a ML model which is trained on a million data set (supervised classification on text) , however I want the same model to get trained again as soon as a new data comes in (training data). This process is continuous and I don't want to loose…
Uma Sankar
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Scikit-learn: How to calculate the True Negative

I am using Scikit-learning and I need to calculate the True positive (TP), the False Positive (FP), the True Negative (TN) and the False Negative (FN) from a confusion matrix like this: [[2 0 3 4] [0 4 5 1] [1 0 3 2] [5 0 0 4]] I know how to…
Euskalduna
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Unseen nominal values in weka

I have a dataset with some nominal values as features. The training set I have has a set of values for the nominal features which are absent in my test set. For instance my feature in the training set corresponds to @attribute h4…
DaTaBomB
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Supervised Learning on Coding Style - Feature Selection (Scikit Learn)

I am researching whether or not it is possible to automate the scoring of student's code based off of coding style. This includes things like avoiding duplicate code, commented out code, bad naming of variables and more. We are trying to learn…
stogers
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Why isn't DropOut used in Unsupervised Learning?

All or nearly all of the papers using dropout are using it for supervised learning. It seems that it could just as easily be used to regularize deep autoencoders, RBMs and DBNs. So why isn't dropout used in unsupervised learning?
MWB
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How should I teach machine learning algorithm using data with big disproportion of classes? (SVM)

I am trying to teach my SVM algorithm using data of clicks and conversion by people who see the banners. The main problem is that the clicks is around 0.2% of all data so it's big disproportion in it. When I use simple SVM in testing phase it always…
rvnikita
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When to use supervised or unsupervised learning?

Which are the fundamental criterias for using supervised or unsupervised learning? When is one better than the other? Is there specific cases when you can only use one of them? Thanks
Daniel Amaya
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What is the difference between classification and pattern recognition?

Could someone explain the difference between classification and pattern recognition as simply as possible or direct me to the right place?!
mhdella
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Training Tagger with Custom Tags in NLTK

I have a document with tagged data in the format Hi here's my [KEYWORD phone number], let me know when you wanna hangout: [PHONE 7802708523]. I live in a [PROP_TYPE condo] in [CITY New York]. I want to train a model based on a set of these type of…
Hamman Samuel
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How to count decision tree rules in R

I employed RPart to build a decision tree. Without a problem, I am doing this. But, I need to learn (or count) how many times the tree has been splitted? I mean, how many rules (if-else statement) the tree has? For instance: X …
user3692479
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How to add more features in multi text classification?

I have a retail dataset with product_description, price, supplier, category as columns. I used product_description as feature: from sklearn import model_selection, preprocessing, naive_bayes # split the dataset into training and validation datasets…
Snow
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Naive Bayes in Quanteda vs caret: wildly different results

I'm trying to use the packages quanteda and caret together to classify text based on a trained sample. As a test run, I wanted to compare the build-in naive bayes classifier of quanteda with the ones in caret. However, I can't seem to get caret to…
JBGruber
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