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An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.

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7 views

Predict output sequence one at a time with feedback

I would like to solve the following classification problem: Given an input sequence and zero or more initial terms of the true output, predict the next term in the output sequence. For example, my ...
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11 views

Classification of religions in Azure Machine Learning Studio

I'm creating a classification model from the UCI Flags dataset where the goal is to predict the religion of a country from the features of its flag. I'm using Microsoft Azure Machine Learning Studio ...
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12 views

Input data for this dataset to be feed into keras for training

Suppose I have 3 csv files which forms the dataset for training a machine learning model in Keras. file1.csv ...
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1answer
7 views

Can I use fit() function with images in Keras?

I want to use vgg16 to train a dataset that contains images. Can I use fit() function instead of fit_generator() in Keras? How?...
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1answer
18 views

Logistic Regression or regression SVM for probability of outcome

I am working on a prediction question: what's the percentage of Y = 1 using a number of features? The output Y values I have for training are in binary. In this case, should the prediction be ...
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0answers
9 views

NLP research: Emotive conjugation

Is there any formal NLP research into emotive conjugation (aka Russel's conjugation)? Here are some examples of emotive conjugation by Bertrand Russell that are shown on the Wikipedia page: I am ...
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0answers
12 views

Reinforcement algorithm for binary classification

I am new to machine learning, but I've read a lot about Reinforcement Learning in the past 2 days. I have an application that fetches a list of projects (e.g. from Upwork). There is a moderator that ...
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1answer
12 views

How do you classify groups when the inputs are paired?

My data is like this: there is a choice between two alternatives and the customer chooses one. Each time the alternatives are different. I would like to characterize a desirable alternative. I don't ...
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1answer
6 views

CNN to learn and visualize 2d features

In the paper Large-Margin Softmax Loss for Convolutional Neural Networks the author has a figure as below: He is claiming that he is using only 2d features to classify MNIST with a CNN. How is he ...
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19 views

How to best estimate the coefficients of a confusion matrix in case of strong class imbalance?

I have a trained binary classifier (forget about how this was trained and think of it as a magical black box) and I would like to measure its classification performance (e.g. compute a confusion ...
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0answers
32 views

Loss function for Hierarchical Multi-label classification

I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels (e.g., a simple MLP branch inside a ...
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2answers
27 views

Evaluating clusters (e.g. built by kmean) using Random Forest

I have made clusters for my data set (1.5 million samples and 800 features) using k-mean. I am aware of internal indices for evaluating clusters. However, I was thinking about training a supervised ...
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1answer
23 views

How to verify hand written signature?

I trying to create a model for determining whether a questioned hand written signature matches known signature samples, and predict if the signature is genuine or forgeries. I'm guessing I'll have to ...
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1answer
19 views

How to do face recognition without using any kind of Neural Networks like CNN?

Is/was there any way to perform face recognition, instead of using the Convolution Neural Network which uses the technique of mapping(encoding) the face using 128-D vector and then using classifier (...
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0answers
21 views

Reuters / RCV1 / RCV2 datasets

I am currently tackling a multi-label classification problem. Where can I find a benchmark comparison of model results using the datasets mentioned in the title? I am interested in other benchmarks, ...
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0answers
20 views

How to classify a dataset into 5 classes even though the performance is low?

I have a dataset of 5 classes with 8 features, say A, B, C, D and E. Now when I try to classify these into individual classes, I get accuracy, specificity and sensitivity of approx 50-60%, which is ...
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1answer
24 views

Can we make two separate models vs one for classification?

Suppose I have a binary classification problem and my data is imbalanced, I can build a classification model using any of the algorithms and use an oversampling or undersampling technique to handle ...
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1answer
23 views

Classification algorithms and deep learning

Nowadays we see a big trends of deep learning and a lot of applications using it . So, I was wondering do people still need to use the classification algorithms (traditionnal machine learning ) ?
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2answers
184 views

Does it make sense to label a dataset manually?

I would like to implement a classifier on a dataset which does not have a label. I've written a script which labels each row of the source file by some specific values like "IF H > 45 && T <...
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1answer
34 views

Improve NER label results on Non-Enlgish text

I am working on some Medieval Latin text and was using various methods of NER such as CLTK (Latin Model), Spacy (Multilingual, Italian, Spanish Model) and StanfordNER (Spanish Model). When I used the ...
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1answer
12 views

How to give importance to recent data in a large dataset

I am solving a binary classification problem which is also partly a time-series problem. This means that recent data is more relevant than old data. But how can I assign more importance to the recent ...
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1answer
20 views

Entropy in a closed box

I have not understood why the maximum number of binary questions needed to reduce uncertainty is essentially log(T). If i have a ball in a box and 10 possible classes, is it enough to ask log(10) ...
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1answer
43 views

Using class weights in Keras with multiple binary outputs which are not simply one-hot-encoded

My labels are binary vectors of length 5, e.g., [0, 0, 1, 1, 1]. My label set is very biased, 1-to-50, where the case [0, 0, 0, 0, 0] is very common while all ...
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1answer
29 views

Fast and/or memory efficient classification solutions

I'm working on a classification problem with a very large dataset (a little under 1 billion obs) and around 25 predictors. I'm doing this analysis in R on a VM with 128GB of memory, but am still ...
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1answer
28 views

4 Class Classification - Machine Learning Model

I have a data set which contains nearly 150 features and 60k data. And my target feature is continuous variable represents hours. I divided this period into 4 categories of user engagement (4 ranges ...
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28 views

Is my model overfitting when I add new features?

I'm working on simple 2-class classification problem. Nearly all features we have used (except one) are about the same for both classes: A random forest classifier confirms that one feature has an "...
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0answers
18 views

Knn linear decision border

I've grab intuitively why for high values of k the decision border of Knn classifier tends to be linear, but i'm not able to understand it rigorously. Can you help me ? Thanks for your time
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1answer
14 views

Bayes Classifier as a general model

Is it correct to argue that the Bayer Classifier is an ideal classifier, which is taken as a model by every other implemented classifier?
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2answers
27 views

Ordinal Attributes in a Decision Tree

I'm reading the book Introduction to Data Mining by Tan, Steinbeck, and Kumar. In the chapter on Decision Trees, when talking about the "Methods for Expressing Attribute Test Conditions" the book says ...
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0answers
8 views

How to understand when partial dependence plot and feature importance don't agree

I'm checking partial dependence plot and feature importance on my binary classification using gradient boosting. The top feature based on the feature importance is a flat line at partial dependence ...
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1answer
14 views

Poor Precision-Recall curve for binary classifier trained on balanced data, with imbalanced test data

I have an very imbalanced dataset (9:1), for which I have performed under-sampling and achieved a balanced training set (~130k samples total post balancing). I am performing classification using ...
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1answer
16 views

classification performance metric for high risk medical decisions

What is the best classification performance metric for risky medical treatments like surgery? for example a patient should NOT suggest a surgery (negative) if he/she can be treated by medicine (...
5
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1answer
55 views

Make classification and prediction at the same time

I am working on the detection and prediction of epileptic seizures and I was thinking about something : would it be possible to apply classification and prediction at the same time. I mean, having ...
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0answers
26 views

Explaining ROC curve

I am running classification algorithm on binary class classification problem where I achieve ~85% precision and ~84% recall rate. My issue is that ROC score looks quite edgy and there are only few ...
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0answers
17 views

Samples that share same features but have different labels/output values

I have built a clustering model based on numerical data, specifically time series clustering. Let's say using sales quantities (over time) of different products. In other words identify different ...
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0answers
6 views

How to build a sentence qulaity estimatior?

I am working on a problem where I need to predict sentence quality(say if a sentence is well written then 10,moderately written then 5 and if too many mistakes or poor formation 1/2 on a scale of 1-10)...
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2answers
37 views

how to measure the uncertainty of prediction

Given a multiclass classification model with n features , how do i measure the uncertainty of the model for that particular classification? Lets say that for some class the model accuracy is amazing ...
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1answer
20 views

Convert nominal to numeric variables?

I am trying to develeop an algorithm with sklearn and Tensorflow to predict which car can be offer to each customer. To do that I have a database with the answers of one survey to 1000 customers. An ...
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0answers
15 views

Rather use many linear classifiers than one complex one for numerical data?

I need to classify machine data (sampled by the second) and I need a prediction if a signal is good, medium or bad every ten seconds. The data that I got from the machine at the moment look like this:...
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1answer
25 views

How to deal with unbalanced class in biological datasets?

When dealing with unbalanced class, which is better, oversampling/undersampling of the classes or randomly selecting equal number of positive samples and negative samples from the training dataset ...
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2answers
29 views

Why does prediction by a consensus of classifier work better than prediction by a single classifiers?

I have seen that consensus of classifiers (taking say 5 separate classifiers) and obtaining the final labeling of the unknown sample based on the voting method (whichever class gets the predicted the ...
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2answers
16 views

How to handle NaNs for ratio feature for binary classifier?

I'm creating a churn model and would like to create a ratio (# customers / total transaction) for each merchant. About 70% of the data are NaNs (zero/zero). I was wondering what I should impute for ...
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2answers
51 views

How to select features for Text classification problem

I am working on a problem where we need to classify user query into multiple classes. Problem: Suppose we are running a website for selling products. The ...
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2answers
31 views

How would you deal with inf. or NA for rate or ratio as a feature variable

I'm trying to create a feature for a churn model (binary classifier). The feature is mean of sales growth rates for several months. But if I just take the mean of sales for several months, I often ...
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1answer
27 views

application of CNN in genomics

Since CNN has been widely applied in DNA sequence data, I'm wondering why CNN is not often used for predicting phenotype from SNP data, given that SNPs are essentially parts of DNA sequences and ...
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1answer
26 views

Some confusions on Model selection using cross-validation approach

https://stats.stackexchange.com/questions/11602/training-with-the-full-dataset-after-cross-validation explains the procedure and the importance of doing cross-validation to assess the performance of ...
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1answer
33 views

Skills based recommendation system

Assuming that I have a list of Users with a list of skills: (each value is a different skill) And a list of Tasks with a list of demanded skills: Based on a manual classification that returned: (...
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0answers
12 views

How to design samples in training set

I have to optimize the execution time of a program (p \subsetof P) which can be configured in 'N' ways. I plan to use a classifier machine learning model, as 'N' is very large, so manually trying each ...
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1answer
17 views

Binomial family in logistic regression

I was asked in an interview why do we use the binomial distribution in logistic regression and how is it related to the class that we are predicting? Could anyone explain, without any mathematical ...
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1answer
30 views

How to show value of a classification model even though it doesn't get the desired performance?

I developed a classification model for a telecom client. Where we classify between Dual-sim and non-Dual-Sim clients. After many iteration the best precision we can get is 60%. The contract says that ...