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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9 views

Prediction using categorical, binary and time series variables

I have per subject: categorical variables - ex: grade, mother_education continuous variables - ex: ...
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8 views

Decision Tree English Rules and Dependency Network in MS SSAS

I created a Decision Tree model in Microsoft Analysis Services (SSAS, Visual Studio 2010). There are two tabs in the Mining Model Viewer tab: (1) Decision Tree that shows a tree itself, and (2) ...
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9 views

Why is MeanDecreaseGini over 1 in RandomForest package in R? [duplicate]

I am using R package randomForest, and calculated MeanDecreaseGini as below. ...
2
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1answer
11 views

Using variables that are only available for part of the data-set in a classification model

I have Data X1, X2, and y. X1 has the same variables as X2, + some extra variables that X2 does not have. I want to use the data X2 to predict binary variable y. I suspect the extra variables In ...
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24 views

Classification algorithms for handling Imbalanced data sets

I’m working on a classification problem where dataset is extremely imbalanced ( roughly 13000 "zero" and 100 "one" responses). As the first step, I trained a Logistic Regression and changing the ...
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1answer
27 views

using training data in final model output

I have customer data for around 400,000 customers where 270,000 of them are current customers and 130,000 of them are past customers who churned, what I am doing is classifying them as 0 (non-churn) ...
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1answer
17 views

biased random guess classification

I try to get used to some classification methods in R (kNN, Decision Trees, SVM) and I am just wondering: Is there a way to do a biased random guess classification to see the real performance of the ...
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16 views

Extracting addresses from HTML invoices [closed]

I am given a set of a couple of thousands of invoices in HTML format. They are invoices from many years and different products, so they really differ in layout. I need to extract the address ...
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14 views

How to classify a unbalanced dataset by Convolutional Neural Networks (CNN)?

I have a unbalanced dataset in a binary classification task, where the positives amount vs negatives amount is 0.3% vs 99.7%. The gap between positives and negatives are huge. When I train a CNN with ...
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1answer
22 views

Iteratively solving for prior probabilites.

I'm using Bayes theorem to classify data into two groups, where the conditional probability is known but the prior is not. So I assume that the ratio of prior probabilities is 1 and calculate the ...
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1answer
21 views

Stochastic Gradient Descent - how to choose learing rate?

I have a large set of data and I want to train an SGD classifier (using sklearn.linear_model.SGDClassifier) as it's impossible to fit all data in memory.. I am asking to know how should I choose the ...
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4answers
50 views

In practice, why do we convert categorical class labels to integers for classification

This might be a naive question, but I am wondering why we (or maybe it's just me) are converting categorical class labels to integers before we feed them to a classifier in a software package such as ...
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27 views

Calculate the probability of a string

I have a classification problem. I am trying to classify strings using I normalize the data before training. So far I get the best results with addition, but I cannot understand why. The ...
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0answers
27 views

Unclear what to make of test results

I'm attempting to classify e-mails using Mallet and an SVM. Below are some test-results, but I'm not sure what to make of them. The test-set is the most recent e-mails found per project. The ...
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1answer
56 views

What does the k-value stand for in a KNN model?

What is the k-value in a KNN classification model? Is K the number of Clusters?
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1answer
16 views

Extract training data predictions from rpart

I'm wondering if there is any method to extract the class assignment of each sample in an rpart model from the training data? E.g. in R using random forest to get the predicted class of each sample ...
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1answer
35 views

Is summing posterior probabilities valid for classification problems?

A classification for two mutually exclusive problem can be formulated by having a decision hinge on whether $P_0(x) > P_1(x)$ or $P_0(x) < P_1(x)$ where $P_0(x)$ and $P_1(x)$ are posterior ...
4
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1answer
88 views

Is the objective to beat a random classifier when the data set is skewed using PR curves?

I have a testing data set where 1/3 of the observations are class-1 objects and the remainder class-0. Hence, the data set is skewed (skewed classifier), literature suggests that if the data set is ...
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1answer
21 views

logistic regression for weak predictors

Could some one suggest a method for gaining high accuracy with weak predictors in logistic regression? Thanks in advance
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1answer
34 views

image classification R

I have JPG images like below and each one is less than 200 KB. My webcam and the watch are in a fixed position. I want to analyze images and tell the exact time. I have huge number of images and ...
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0answers
26 views

What are the quantitative methods alternative to Meta-Analysis?

What are the alternative statistical quantitative synthesis methods for combining studies, if we can't apply meta-analysis because of the heteronegeity or the shape of the data, for the data set of ...
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40 views

Which method should I use to combine the data of my studies?

I want to make a meta-analysis on household consumption expenditures elasticity data. In these studies that I've got; methods and regions and etc. varies according to studies. But at last, the results ...
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0answers
1 views

Best way to estimate “factor of true classifications of training set” in R

I'm using the knn function from FNN package (similar to class package) in R. I need to set the parameter cl = "factor of true classifications of training set". May you suggest me some ...
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1answer
42 views

combining multiple classifiers common features

Can multiple binary-classifiers be combined to produce a final output if their feature sets have some common elements? How will this influence the accuracy?
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1answer
35 views

How can I derive confidence intervals from the confusion matrix for a classifier?

I have am using k-fold cross validation to generate a confusion matrix for a classifier. I need to calculate 95% confidence intervals for the number of times each class is predicted when run against a ...
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1answer
10 views

is negative log loss affected by oversampling?

I'm working on a multiclass classification problem where negative log loss is the evaluation metric. My initial train set and my static test set have similar class distribution and my validation (20% ...
2
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0answers
14 views

How to traverse the tree structure of rpart object in R? I need to get all the nodes associated with a subtree, how can I do it? [migrated]

I am using rpart for building a decision tree classifier. I wish to use my own pruning function based on certain parameters of the leaf nodes corresponding to a subtree. For this, I think I need to ...
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1answer
17 views

Name and methods for classification with 'unknown' as acceptable result

What is it called when, in a classification task, it is acceptable that some data-points do not receive a label? And what classifiers are suitable? I have a dataset with a two valued target variable. ...
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2answers
49 views

Should image classifier be trained using colormap pixels or the actual value?

For example, I have a population density map of a 100 x 100 km square region. Each part of the rectangular region represents the population density i.e. (1,1) -> 128 people, (100,100) -> 50 people ...
3
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1answer
14 views

Is accuracy = 1- test error rate

Apologies if this is a very obvious question, but I have been reading various posts and can't seem to find a good confirmation. In the case of classification, is a classifier's accuracy = 1- test ...
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0answers
13 views

Non idependence within groups

I have to train a machine learning model for classifying two groups. Unfortunately, my positive group has a small number and many cases are not independent from each other (observations taken in ...
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0answers
10 views

Unbalanced groups and classification errors

I would like to adopt a general strategy for dealing with an very unbalanced dataset, where my "positive" group corresponds to 1/40 of all the observations. The reason why I ask it is because all the ...
1
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1answer
46 views

Threshold selection by intersection of Sensitivity and Specificity

Some days ago, I learned in a lecture that the intersection of Sensitivity and Specificity provides an optimal compromise for choosing a classification threshold for logit or probit models. However, ...
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0answers
15 views

Recommended performance metrics of a binary classifier having an example-based cost matrix

I would like to know what are the recommended performance metrics to assess a binary classifier, when the cost matrix is changing for each sample. My problem comes from the fact that in this case, ...
0
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1answer
41 views

Learning a classifier to compute distance between points for clustering

I have dataset of items and want to cluster them. However, I don't have a predefined distance function. Does it make sense to learn a classifier that can predict the similarity between any two items? ...
0
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1answer
6 views

Anomaly classification probability on Machine Learning

I am using features to predict a dataset classification. I have use the Gradient Boosting Classifier of scikit-learn for the prediction and tune it to reduce the error classification. The error ...
2
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0answers
26 views

ML classification problem for matrix and distribution estimate for each cell in the matrix

I am trying to think about a machine learning/statistical learning related problem. But would love to get idea from people in the forum about related problem/work/resource. So, the problem idea is ...
0
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1answer
19 views

How to detect noisy entries in the data set

I have a data set (entries described by the list of features X1-X7). This data set contains a small percentage of noise. How can I detect those entries that are subject to noise and exclude them from ...
3
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0answers
26 views

Student classification with Multinomial Logit

I’m analyzing student performance data. In my dataset, each row corresponds to a student and each column contains several performance metrics (continuous) and the student type (categorical, 4 types). ...
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54 views

How to validate sentiment classification and compare different algorithms

I need to compare SVM and NB about sentiment classification by evaluating accuracy, precision and recall measures. I have 1500 manually classified documents, and I would know which is the best way to ...
1
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0answers
23 views

Bias the classification in logistic regression

I want to make my classifier prioritise finding true cases (1) even if that means that a lot of the false cases (0) are also classified as true. Specifically I wish to find the weights to my features ...
0
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0answers
8 views

Measure of value change

I would like to know the best way to evaluate which measure changes the least for different data across a class. Exact problem I am facing is that I have a few images of an object and I have ten ...
1
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1answer
50 views

Classification problem-Big Data and simple decision rules: logit regression, LDA, random forest, cond. trees, or something else?

This is a big data question from someone who is more accustomed to small data. I would like to develop some classification "rules of thumb," that is, some simple decision rules or a decision tree ...
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0answers
9 views

Problem with R Caret J48 [migrated]

My code is below: ...
0
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0answers
9 views

adaboost with multiple classification algorithms

Up to now I saw that all adaboost implementations use single classification algorithm and a training dataset as input and then creates multiple classification models by re-sampling dataset and uses ...
0
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0answers
37 views

root cause analysis with random forests?

There are metrics how to determine the most important features in a random forest model (Gini index, permutation accuracy). But is there also an approach how to analyse or visualize the root cause ...
17
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4answers
893 views

What does AUC stand for and what is it?

Searched high and low and have not been able to find out what AUC, as in related to prediction, stands for or means.
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0answers
18 views

Normalization of Naive Bayes output

In Scikit-learn documentation it is possible to see that the MultinomialNB estimator has a method called predict-proba in which it has the following description: "Returns the probability of the ...
1
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1answer
44 views

Selection bias and reliability

I need a bit of help with interpretation of classification results. I have unbalanced data set (80% = 0 20% = 1), fitting classifiers (SVM, GradientBoosting or kNN) on such data does not yield good ...