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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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Treating multilabel as multiclass perfomance

I am struggling to comprehend something. In case of several labels prediction, when multiclass prediction should be prefered over the multiple multi-label predictions? Assume that we have 10 binary ...
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10 views

Classification of time series using rolling window, window size

I’ve been experimenting with time series classification lately and I have some wonderings regarding real-time prediction. Assume “class a”pattern we trained with [0 1 2 3 0 ] Actual data [0 0 1 ...
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6 views

How can stratified kfolds perform worse than regular kfolds?

I am working with unbalanced classes to solve a classification problem (whether individuals pay their fees or not). My class imbalance is 75% positive (paid) and 25% negative (unpaid). I have read ...
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33 views

Handling imbalanced data for classification [duplicate]

What are the best ways to deal with imbalanced datasets for classifying whether or not individuals pay their tuition? The data is 75% positive class (paid) and 25% negative (unpaid). Some approaches I ...
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12 views

Comparing ratios for correlation

I want to classify counties based on disease-food type into multiple zones and suggest medical intervention . Given disease occurrence as a ratio of population of each county. Data is provided with ...
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49 views
+50

SPSS - Binary logistic regression: classification cutoff

Let's say I want to evaluate the predictive value of a continuous variable in the prediction of malignancy (event/status) of a tumour. Malignant = 1 Nonmalignant = 0 In SPSS, I can run a binary ...
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16 views

How can I run a decision tree algorithm with a specific hierarchy of variables and with many missing values?

I asked students in learning groups what their biggest learning problem was "today" for each learner. The biggest problem could either be "motivational" (=motivation problem) or cognitive (="knowledge ...
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20 views

Chicken and egg problem in determining the target feature

I have a large dataset of customers in an online shop, where many features regarding their history of buying behavior are recorded: who bought what, at which time, how often they entered the shop, at ...
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27 views

Sklearn decision_funtion (threshold) choice

According to sklearn documentation one can change the decision_function method in some models to improve results. For instance, if you want a higher recall in a ...
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0answers
17 views

Unbalanced data on fire for a binary classifier

I have a lot of training data from which I want to build a binary classifier, but the classes are highly unbalanced, 97% in one class, 3% in the other (even though, in absolute terms, I still have a ...
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1answer
22 views

How to Interpret AUROC score?

My model has an AUROC value of 0.7, and I have a 75:25 class (75% negative, 25% positive) imbalance. From my understanding, AUROC is calculated by using different thresholds for considering the ...
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6 views

How do I get from being able to answer “Is this a picture of X?” to “Does this picture contain X somewhere?”

I am teaching myself machine learning and I am looking to solve the following problem. My main issue is that I do not know the name of this (or a similar) problem so I do not know how to look for ...
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1answer
12 views

CartPole: Using sigmoid and softmax cause program converge differently [on hold]

I am playing with the CartPole problem. It works but when I switch from Sigmoid to Softmax at the end of the network, as input for multinomial distribution, the program behaves quite differently. ...
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6 views

Bounding Classification Loss Function

I am having trouble to establish some bounds. An exercise asks to me to bound: $$ L(\theta) - L(\tilde{\theta}) \leq C E[\min((X'(\theta-\tilde{\theta})^2,1)] $$ where $L(\theta) = E[(Y-\phi(\theta'...
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17 views

Image Classification using openCV [on hold]

I am currently working on a project, where the problem statement is to detect handwritten text from a image of a particular form. As a pre-processing step I have extracted texts in the form of ...
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2answers
47 views

How to define a time series classification problem?

I have 3 sets of time series data generated from sensors, I believe they have some correlation themselves. Certain "modes" of the system can be defined from the patterns from these signals. The signal ...
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0answers
11 views

SVM optimization problem with constraint

I am studying SVM from Andrew ng machine learning notes. I don't fully understand the optimization problem for svm that is stated in the notes. So we have optimization problem $$\max_{\gamma, w, b}\...
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1answer
35 views

Why are generative and discriminative models called that way?

In machine learning, if I understand it correctly, a generative classifier is one where we directly model the joint distribution $p(x,y|\theta)$, while in a discriminative classifier we model $p(y|x, \...
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1answer
55 views

Why the discrepancy between predict.xgb.Booster & xgboostexplainer prediction contributions?

One way to explain individual predictions of an xgb classifier is to calculate contributions of each feature. To my knowledge there are two packages in R that can do this for you automatically. In the ...
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14 views

Training an autoencoder with reconstruction target and classification labels

I would like to binarily classify a number of sequences which contain heavy noise. For each of these sequences, I have another sequence which is related to it, contains less noise and is also closely ...
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1answer
31 views

Classification Tree or Regression Tree?

I have time series data: students that learned in groups for minimum 3 times and maximum 10 times and for each learning group session had to state if they faced a motivational OR a cognitive problem, ...
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0answers
18 views

Inducing relative class frequency/ soft (voting) probabilities for classification Random Forests in R [duplicate]

(The following question concerns binary classification) As discussed in other posts, when using Random Forests for classification one maybe not just interested in the output class (i.e. 0 or 1) but ...
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20 views

How to classify similar looking dataset but belonging to different class

I've got a user dataset in which there are two classes. The size of dataset if 50,000. Class_A=5000 , class_B= 45000. Now the problem is that there are some instances(500) which though belong to ...
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1answer
107 views
+50

Why is cross entropy not a common evaluation metric for model performance?

When we train a classifier, we use cross entropy as a loss function and, for example, an F-Score as an evaluation metric, but why? Why not use cross entropy on the test set to evaluate the model ...
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20 views

Classifying objects based of a varying number of the same type of feature vector for each object

For a congressional session, I have created a doc2vec model of speeches made. Using the vectors from this model, I have a dataset of each congressperson, their political affiliation, and a list of the ...
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7 views

What should be the properties file for IOB tagged Dataset for using in Stanford Open NLP NER Tagger?

I've created dataset like Jone B-PER Smith I-PER is O a O good O man O in O Luis I-LOC city O . O I'm using this settngs ...
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25 views

How to test a PCA+classifier model? [duplicate]

I have a 100x45 dataset and I'd like to perform feature selection and classification/regression. I'm currently using various techniques to check which one has the best performances, but I have a ...
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20 views

How to manually balance unbalanced multi-class/multi-label data?

I have a multi-class and multi-label classification problem, i.e.: each sample can have more than one label associated to it and there is a total number of M ...
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0answers
25 views

Determining the number of simulations in non-parametric classification simulation

I am currently working on setting up a simulation study that compares the effectiveness of k-nearest neighbours and gradient boosted trees. I have checked these two sources. Both refer to p-values ...
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1answer
42 views

Knn Decision boundary

I am new to machine learning and trying to draw decision boundary for k nearest neighbor where k=3. I know that the decision boundary for k=1 would be the perpendicular bisector between two different ...
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0answers
8 views

Importance of standard deviation in a classifier

I have two different classifiers that affect the same dataset. I ran a repeated 10-fold cross validation and these are the results: C1: total mean of precision = ...
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0answers
10 views

Testing if word-count vectors follow a multinomial distribution

I am attempting to make a Naive Bayes classifier for word count vectors (each document is represented as a vector of word counts). For this, I am using SciKit-Learn's MultinomialNB. From what I ...
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0answers
9 views

Mathematically applying regularisation to logistic regression to reduce over fitting

I recently was introduced to the concept of regularisation to reduce the process of overfitting in logistic regression were the curve fits too perfectly to a point where our non linear line does a ...
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6 views

Classifier for data with multiple entries per user

I'm working with a dataset that contains certain data about the users (e.g. address, marital status), along with clicks they made on a certain platform, with timestamp for each click. Overall there ...
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11 views

Which type of feature scaling should be used?

I have 11 features with categorical values [1and0] and 4 features with price in dollars. So ...
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1answer
36 views

Linear discriminant analysis with $p\gg n$

I am studying Linear Discriminant Analysis (LDA). According to the formula for LDA, we are supposed to get the inverse of within group covariance. However, if $p\gg n$ (i.e., the dimension is much ...
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6 views

Nonparametric classification of a sample of values — is my approach correct?

Suppose I have a machine with a number of different labelled settings. The labels go from $1$ up to $L$. When I choose a setting on the dial, let's say setting $j$, I can have it output i.i.d. samples ...
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1answer
21 views

Classifying compositional vectors of time series

I am interested in classifying vectors of time series $x_t=(x_{1,t},\ldots,x_{n,t})$. In addition these vectors are subject to the restrictions $\forall i,t$: $0 \leq x_{i,t} \leq 1$ and $\forall t$: $...
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10 views

What does it mean to “derive” a classifier?

As in, what is the difference between a "derived" classifier and one that is not derived?
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20 views

What features to select from the dataset for classification? [closed]

I have been doing a classification task and I've tried multiple algorithms with GridSearchCV to parameter tuning and I still can't seem to get a higher score. So I ...
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0answers
41 views

validation AUC systematically under 0.5 [duplicate]

I'm training a model with lightgbm (but I have the same behavior with linear regression and random forest). I'm trying to figure out what is causing this strange training behavior. Here my iteration ...
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8 views

Classication given several softmax probabilities

I am classifying images over time in categories such as office, bathroom, living room, etc. using CNNs (in this case VGG-16). The idea is to use all room categories' confidences (softmax probabilities)...
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1answer
45 views

Decision tree without the “tree”

I would like to construct something like a decision tree. However, instead of using "recursive partitioning" to build a tree, I would like to find an optimal set of "global" splits. For example, in a ...
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1answer
18 views

Merge one label with one information for classification problem or multi-label classification

I want to build a model to support decision making in order to propose or not loan insurance to clients. Because sometimes clients asking loan and loan insurance have less chance to have their loan ...
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0answers
26 views

Using Hidden Markov Models for Classification

When we use HMM for classification, we need to train one HMM per class. My question is: How to find the matrices A,B,\pi?? What is the meaning of them? To clarify: A =[aij] transition matrix, aij ...
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1answer
102 views

Bayesian networks for one-class classification

From the definition of one-class classification in wikipedia: In machine learning, one-class classification, also known as unary classification or class-modelling, tries to identify objects of a ...
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0answers
20 views

Correct cross-validation procedure for single model applied to panel data

Questions What is the correct CV procedure for panel data? I've been thinking of the problem as cross-validating a model fit to multiple time series data. Is the "population informed" CV procedure ...
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1answer
19 views

Other distances than euclidean distance in knn [closed]

Suppose I want to fit a k-nearest-neighbour using caret package in R: ...
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0answers
30 views

Calibration of penalized (LASSO or ELasticNet) logistic regression models

I would be very grateful for any help me with the following general query regarding calibration of penalized models with a binary outcome. I would like my prediction model to be calibrated (mean ...
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0answers
28 views

Classification model on a highly unbalanced dataset [duplicate]

I’m dealing with a highly unbalanced dataset where 20% of data belongs to class A and 80% belongs to class B. It’s very hard for us to produce synthetic class A data. Just wondering if the below ...