Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a ...

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14 views

Detecting discontinuities in irregularly-spaced data

I am running physics simulations. Sometimes a simulation has insufficient resolution and produces discontinuities in the output variables. These are very easy to spot by eye in a scatterplot. I would ...
0
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0answers
9 views

Correct evaluation/ comparison between undercomplete and overcomplete representations

Suppose I'm performing Unsupervised Feature Learning method to learn a representation of the data that is under-complete (e.g. 100 features) and use another algorithm to learn an over-complete ...
0
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1answer
34 views

output is a factor … how do I model it

If my input is numeric and my output is continuous I can use linear or nonlinear models. I can split the inputs by factors if an input is a factor. If my input is numeric and my output is boolean I ...
0
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0answers
10 views

Analysis of classification result

Assume you observed a system for 24 hours and collected data points each minute (each data points contain some host information like cpu_usage,... All elements are numeric). Also, there is a trained ...
0
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1answer
15 views

How to calculate the probability that a scalar data point maps to a class?

Suppose that I have the following data set that maps students' test score to the class in which the student belongs: ...
0
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0answers
22 views

Comparing classification accuracies with different numbers of features

I have a classification problem in which I’m trying to assign a label to each of a collection of inputs x_i. I’m comparing two different feature representations of the inputs, trying to determine ...
0
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0answers
20 views

Using glmnet/lasso to tune a logistic regression model [on hold]

I am trying to make a logistic regression model using the lasso technique. I have 56 potential predictor variables (IVs), and I would like to use lasso to select a parsimonious set of predictors. The ...
0
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0answers
17 views

Can I create a convolutional neural network with this data?

I have a dataset of 80 CT scan images and want to use a convolutional neural network (conv net) for classification. I was thinking of taking 40 images, augmenting them with 5 degree rotations over 360 ...
1
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0answers
29 views

Cost function: output layer should sum up to roughly 1

I have a convolutional neural network classifying some images for me. The output layer is not one-hot encoded but outputs a distribution around the predicted class (because neighboring classes are ...
0
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1answer
7 views

Non-biased User Interface for building training set

I want to use machine learning to detect objects of type A among objects of types B-Z. I require human expertise to initially classify these objects as A, B, C... Z. The individuals who can provide ...
0
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0answers
15 views

Calculate statistical significance in natural language processing

I have a task to say whether the difference in performance between two systems is statistically significant. The task is similar to sentiment analysis. I have sentences and I need to classify them ...
0
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0answers
13 views

Can two Classifier with different number of False Positives have exactly same ROC curve?

There are two classifiers, the first one return Scores ...
0
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0answers
10 views

Can neural network on outliers data have 100 percent error in classification? [closed]

I train the neural network on outliers data. Is it possible to be 100% error? What is 100 percent error causes neural network?
0
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1answer
19 views

Validation of Support Vector Machine using sklearn

I have made a recording of two different sounds and I want to use an SVM in order to be able to distinct between the two. The process I have followed is: Divided each sound in multiple 20ms frames. ...
0
votes
1answer
34 views

SLP vs. MLP: Is my data linearly separable?

I implemented an artificial neural network using scikit neuralnetwork. As default configuration for my classification task I am using 10730 Datsets x 115 Features 1 Hidden Layer with 61 neurons 7 ...
0
votes
1answer
46 views

Neural network: two output vectors?

Architecture: I have a CNN which does some classification for me. The output layer y consists of a vector $\vec{y}$ which is of dimension $(1, 1000)$, so it has 1.000 neurons in total (the weight ...
1
vote
1answer
14 views

Should I perform parameter tuning on the balanced or imbalanced dataset?

Consider a binary classification problem. As far as I know, if the dataset is imbalanced and if the two classification errors are not equally serious, then we should balance the distribution of the ...
0
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0answers
8 views

Identifying important differences between supervised learning datasets

The training data in a multi-class supervised learning task shows a significant dependence on time that is apparently not captured well by my learners. Specifically, the two learners I used (OvR ...
0
votes
1answer
23 views

Computing the Interaction gain. Is there an Error in the infotheo package in R?

In order to implementing a certain feature selection method for a classification problem I need to estimate the the interaction the interaction gain between two features and the target variable which ...
1
vote
1answer
44 views

Can a confidence interval be greater than 1?

I am doing a classification task and obtain an accuracy of 97.5%. Now, I calculated the confidence interval, assuming a normal distribution, at the 95% confidence level with: Accuracy +/- ...
0
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0answers
7 views

How to test if data imbalance affects classification results

My data is imbalance with say 80% of class A and 20% of class B. Training and Test results look OK e.g more than 90% of accuracy for both classes. Assume I want to improve the results. I wonder if ...
0
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0answers
35 views

Build HMM of text data in R

I'm trying to make my own HMM tagging in R but don't know how to estimate parameter values since the packages I have been working with haven't worked with my data. The latest package I have been ...
1
vote
0answers
15 views

What algorithm or implementation would classify a set of data into one of two groups? [closed]

My data is in the form of long lists of integers of indeterminate length and where the position/order of the integers in the list doesn't matter, which can be assigned to one of two categories. E.g. ...
3
votes
0answers
28 views

PCA to decorrelate and classify timeseries

I have a labeled dataset where each subject belongs to one of two classes A or B, with A ...
2
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0answers
21 views

which classifier to choose for probability histogram-like features

I have a populations of 500 elements. Each element is represented by a 10 dimension feature vector which sum of element is equal to 1 (you can think about it as a histogram of probabilities). In ...
0
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2answers
31 views

Classification with a neural network when one class has disproportionately many entries

I try to train a neural network using a dataset with several classes $c_1, c_2, \dotsc, c_{10}$. The class $c_1$ has a lot more entries in the training set than the other classes, and this makes my ...
0
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0answers
40 views

Confused Scikit results

I am doing classification machine learning on a particular dataset on which an SVM model (using Scikit.learn) is giving a Matthew's correlation coefficient (MCC) of ...
3
votes
1answer
14 views

How to deal with data in which users_ids belong to more than one category (Multilevel) using Random Forest?

I know it sounds trivial, but I could not find any ready answers for this. Suppose we have this kind of data and we want to predict some target values for several users. ...
0
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1answer
33 views

Classifier performance [closed]

I have some data that are training data. the feature size of training data is n but feature size of my test data is m. which one of classifiers can do classify this data?
0
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0answers
19 views

Evaluating performance Neural Network embeddings in kNN classifier

I am solving a classification problem. I train my unsupervised neural network for a set of entities (using skip-gram architecture). The way I evaluate is to search k nearest neighbours for each point ...
2
votes
1answer
32 views

Converting between different accuracy/error metrics

I am trying to compare model accuracy between several different measurement metrics. For example, some citations use accuracy while other use error. That one is rather obvious, but there are lots of ...
0
votes
0answers
9 views

Classification techniques for handling mislabeled data

I am trying to think about a problem of how to model binary data in the presence of possible labeling errors and was curious if anyone had any thoughts about it. The basic setting is that we have a ...
0
votes
0answers
10 views

Can I compute ROC AUC of F-measure for multi class classification? [duplicate]

I know ROC AUC is computed for binary classification, as well as F-score. But for multi - class classification, is it possible to calculate ROC AUC or F-score?
0
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0answers
14 views

How many percent in classification accuracy could be considered as significant

I have 2 classification methods to classify 6 classes. The method 1 achieved the accuracy = A1%, and the method 2 achieved A2%, with A2 > A1. How many percentage point between A2 and A1 could be ...
0
votes
0answers
12 views

Difference between Nearest Neighbour and Nearest Centroid

I'm trying to understand the difference between Nearest neighbour classifiers and Nearest centroid classifier. Using the nearest neighbour, one selects a data point ...
5
votes
0answers
33 views

State of the art in general learning from data in '69

I'm trying to understand the context of the famous Minsky and Papert book "Perceptrons" from 1969, so critical to neural networks. As far as I know, there were no other generic supervised learning ...
1
vote
2answers
47 views

Is decision tree output a prediction or class probabilities?

A Random Forest works by aggregating the results of many decision trees. Recently, I was reading about how the RandomForest aggregates the results, and it made me question whether the results from ...
0
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0answers
7 views

How to compare multiple non-hierarchical classications of the same dataset

I'm a taxonomist working on an identification consistency project in which a couple dozen researchers were asked to manually classify the same set of images into like groups. Each classification will ...
1
vote
2answers
50 views

Classifying time-series similarity - what variable should I train on?

I have ~10,000 time series, each with 65 time points. I'm interested in classifying each pair of time series as "similar" or "not similar". Here's an example of two similar (left) and not similar time ...
0
votes
1answer
49 views

data normalization after dimension reduction for classification

The classifier is KNN or RBF-SVM. After doing dimension reduction (e.g., PCA, LDA or KPCA, KLDA), does it need to do normalization before classification? In LIBSVM ...
-1
votes
0answers
19 views

Automatic mail classification

I'm building a mail classifier in Python 3. I've successfully built classifier to classify spam/ham using SVM (LinearSVC to be precise) using scikit-learn. But the next challenge is to auto bucket the ...
2
votes
1answer
75 views

detect incorrect term in group of terms

I obtain a 'group' of numbers every day. Each number is associated with a 'term'. eg 35 is Big Data. 42 is Hadoop, 82 is Zebra, 89 is Python, 3 is Machine Learning, and 6 is Waterfall, etc. I want a ...
0
votes
1answer
24 views

Logistic regression using ANOVA kernel in SKLearn?

In RapidMiner, you can run a logistic regression classifier with multiple kernel types. I see no options in sklearn.linear_models.LogisticRegression. Does anybody ...
0
votes
0answers
17 views

Valid procedure for binary classification with cross validation

I have inherited a classification model for a binary parameter and have been asked if estimates can be improved. From this model, an equation has been put into some software for predicting this ...
3
votes
2answers
25 views

Features, samples, and over-fitting?

I have a data set with 30 samples, 2 classes, and 100,000 features. When I run an SVC classifier on it from SKLearn using stratified cross-validation, the accuracy is barely better than chance. After ...
0
votes
1answer
15 views

Ground truth Vs. Baseline [closed]

I was wondering what the difference between ground truth and baseline is? Is it necessary that a system should always be tested ...
0
votes
0answers
34 views

Interpretation of partial dependence plots for multinomial GBM

I've been a big fan of the gbm package for some time, but am having difficulty understanding the output from the partial dependence plots in the case for multinomial classification problems. Below ...
0
votes
0answers
7 views

Content Based Document classification

I have a corpus of 10 million resumes. I want to add tags to these resumes like Software Engineer, Data Scientists, ...
0
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0answers
22 views

How to compare the feature importances produced by two different classifiers?

In one study, I am using two different classifiers. I want to compare the feature importances produced by two classifiers. Is there a statistical technique to measure the similarity between the two ...
0
votes
0answers
9 views

Junk data in classification

I have a data set which I would like to classify it into two classes. And I have training data for each of those classes. However there is also junk data which I also have some samples but since it's ...