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Questions tagged [classification]

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 variable behavior which can be studied by statistics.

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Is there a specific or standard definition for what classes as a peak?

I am working on some peak analysis at present, essentially just a programme that will identify peaks in a histogram and return the graph with those peaks pointed out. My question is, is there a ...
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15 views

flight delay prediction [on hold]

Suppose that there is an airport and we have the average of flight delays for every day of the first month of 2018. Lets say the first day had an average flight delay of 2000 seconds and the second ...
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3answers
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How can I understand the concept of a noise in machine learning?

In Bishop's book, one of the first examples is shown here Essentially, the data $x$ are randomly generated, and $t$ are generated by running $x$ through a function $\sin(2\pi x)$, then Gaussian ...
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20 views

Does BoxCox transformation work for logistic regression?

I'm working on a case study from this MIT course. I'm practicing classification problems. Here is the code for my model. (The dataset can be accessed from the link. I can add it to this post) ...
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8 views

Impact of C on geometric margin in linear SVM

Will the geometric margin always decrease if we increase $C$ in a linear SVM? When data is linearly separable, that makes sense but I can't really see it when we have nonlinearly separable data.
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14 views

SVM favouring one of the two classes

I have a binary classification problem (class 1 and class 0). I need to place the hyperplane such that it avoids ...
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0answers
18 views

Why isn't accuracy of binary classification model improving? [duplicate]

I have a data set with a binary response variable, about 30,000 observations of 8 features, some are continuous and some are categorical. This is an imbalanced data set, the ratio of negatives to ...
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15 views

Interpreting units for random forest variable importance

I've trained a random forest for classification in R's caret package using the ranger method and impurity for measuring variable ...
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1answer
26 views

Correcting sample selection bias of binary classifiers

In fraud investigation the number of detected fraud cases can be very small when compared to the total number of cases. This would also apply to rare desease detected in a very small number of people ...
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26 views

Multiple comparisons correction in between-subject classification analysis

I am working with a dataset of 46 subjects (23 controls and 23 patients) fmri brain t-maps each with 4 experimental conditions. The main purpose of my analysis is to find the highest classification ...
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0answers
12 views

How to choose the best algorithm to fit neural model [on hold]

Im beginner in machine learning .. I have a problem of classification and i want to fit a neural network model with R and using the function Neuralnet(). but i don't know what is the best algorithm to ...
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0answers
13 views

RFE-RF for non-ordinal multi-class problem using integer target variable

For a classification problem with numerical predictors and a categorical multi-class response I am trying to use Recursive Feature Elimination with Random Forests to identfy relevant features out of a ...
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0answers
22 views

Machine learning to detect wear on a machine axis

I have a machine that moves with one axis in the same direction (basic position A to end position B). While driving, the torque is measured and recorded every 10 milliseconds. This looks something ...
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Calculating the margin of error on an estimated total number of class instances in population

I have a completely random sample of size 10 from a population of objects (population size 1000, if that helps) which can belong to either one of two classes, A or B. Based on a guess from superficial ...
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1answer
23 views

using decision tree to describe high dimensional data

I have a dataset with 6 numeric columns and one dichotomous factor contain yes and no. I would like to understand when yes is more likely given the 6 numeric columns. I intend to use a decision tree (...
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1answer
31 views

Question about making prediction with only two variables

I have a data set with only two variables, student id and book id. I have train and test sets and I will make prediction about what book student will get next time. Should I attach dummy variables to ...
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1answer
46 views

Running XGBoost with *highly* imbalanced data returns near 0% true positive rate. Tried SMOTE and it did not improve much. What else can I do?

I'm using XGBoost on a dataset of ~2.8M records of hard drive failures, where less than 200 are tagged as failures. After cleaning, there are 11 features in this dataset. Below is my ...
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0answers
24 views

How to approach memory issues with up/down-sampling problem across millions of rows in database that can't be loaded locally? (class imbalance)

I'm faced with fairly typical class imbalance problem across a dataset with nearly 9MM rows (hard drive failures) that's not stored locally (it's in Postgres table; downloading a .csv of it is not ...
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1answer
26 views

What does each cluster represent?

I have a dataset from a questionnaire with over 10000 rows and 30 variables. I am trying to have an insight of the data so I tried to cluster similar items. I first made a dimension reduction ...
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0answers
36 views

How does Google Photos face recognition use user-provided labels?

I'm working on a toy project which I think is analogous to the problem of detecting faces and assigning names to them in Google Photos, so I've been thinking about how that process might work. From a ...
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Do I need to treat class imbalance before preforming RFE (Recursive Feature Elimination)? [duplicate]

I am trying to perform RFE on an imbalanced data set that will later be used for binary classification. I have chosen to use the caret::rfe package for feature selection. I am using random forests ...
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0answers
16 views

SVM training yields too many (or no) support vectors

So I implemented a support vector machine, using either a linear kernel or the rbf-kernel. I trained and tested it on a two dimensional set of data and everything seems to be working fine. However, ...
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1answer
20 views

Is LDA just selecting the minimum Mahalanobis distance?

I have a question regarding Linear Discriminant Analysis (LDA). I know that LDA chooses the coefficients of a linear model, which maximize the separability of classes - that is the ratio of "between-...
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22 views

Classification where classes do not use all features?

I am attempting a classification task whereby the features used to describe classes are not all being used. For instance, Class A does not use feature 2, class B does not use feature 4, and class C ...
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1answer
49 views

What is the name for this classification algorithm?

Can you help me find the name of this classification method: Assume we have the following data: $n$ dimensional feature vectors we want to classify in two classes. We model the classes as two $n$ ...
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18 views

Evaluating binary classifier model. What can say precision, recall etc.? [duplicate]

i'm trying to understand wether my model has good performance or not. I have binary classifier for summarization sentences: important or not (extractive approach) on specific corpus. Dataset is ...
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27 views

ML - Text input data

I'm trying to explore an use-case in ML but stuck at a point. May i please request your advise please. Have a service desk web application for logging tickets, which is essentially a form having ...
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0answers
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Restrict Decision Trees For Interpretation

I created a regression tree which predicts wheter people will buy an product or not. The tree is very accurate, but it is also very large and has a depth of 200. When you want to learn something from ...
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Deciding on split points

I have an input variable[x] which is continuous and another output variable[y] which is categorical with two categories[Good, Bad]. I am wondering if there is a scientific way to find the split ...
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2answers
60 views

if there's no noise, is overfitting possible?

Just what the title says. In every model we try to approximate a function $$Y = f(X) + \epsilon$$ Assume we that $Var(\epsilon)=0 \forall X$. However, the train/test set correspond to different sets ...
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0answers
19 views

Can we interpret the value of a Discriminant Function as a probability?

Suppose I have fit a classification model through Genetic Programming. The output is a symbolic expression that is a function of the covariates, and that associates to each data point a class, such ...
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0answers
14 views

Logistic Regression(multi class) accuracy too small

I try to solve a problem with 3 features and 6 classes(label). The training dataset is 700 rows * 3 columns. I use one-Vs-all method, but I do not why the prediction accuracy is too small, just 24%. ...
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0answers
7 views

Predicting Daily Binary Variable with Mostly Monthly Variables

I have a binary classification task with a dataset composed of a time series of independent events. As part of my data augmentation efforts, I have found a lot of economic indicators that however ...
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0answers
10 views

Does it Matter if Categorical Features are Standardized?

I have a dataset I am scaling in order to run a machine learning algorithm. I know it's bad practice to standardize binary features in regression, but I was wondering if it actually makes a difference ...
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How does C4.5 handle missing values and how does it handle weights on attributes

I'm trying to make a implementation of the C4.5 decision tree algorithm, but I cannot find anywhere in detail how C4.5 handles missing values and how it integrates weights on attributes.
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1answer
52 views

Is this dataset lineary seperable? How can I find it out using (linear) algebra?

I have this dataset: I want to know if it is linearly separable (fully separable). I want to use this rule, but I'm not sure if it's correct: Make $X'$ - matrix with d+1 column of all 1's. Then ...
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0answers
13 views

Interpreting probabilities from image classifier, which model to use?

I'm trying to interpret examples from a probability perspective and my intuition is telling me Logistic Regression should be used for such a purpose despite the score being weaker than the other ...
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0answers
15 views

Way build a ML model with dynamic dataset have dependencies between feasuers- python or node

I need build a model has to predict for the director of a treatment institute What is the recommended treatment for a new patient according to his Personal Information and Difficulty diagnosed: the ...
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interprete and calculate Area Under the Curve of classifier in Matlab using perfcurve?

I hope that somebody could help me with the following question. I would like to calculate the Area Under the Curve (AUC) of a classifier (Linear Discrimiant Analyses). To do this, I am using the ...
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1answer
37 views

Classification with a default class

I have data on ~800 observations that are relatively evenly fit between 5 categories. One of these categories is essentially a 'catch-all' group for observations that don't have any of the defining ...
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0answers
10 views

Why are there differences in recall values when I use GridSearchCV vs classification_report (scikit-learn)?

I'm currently working on a clasification problem through random forest. When I use GridSearchCV, using the parameter scoring="recall", the best_estimator_ is: ...
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0answers
8 views

LS classifier that is based on the sum of error squares criterion

Is it possible given a set of points from two classes to determine the LS classifier that is based on the sum of error squares criterion? I don't ask if it is efficient if it is possible and if yes ...
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0answers
11 views

How to correctly plot the outputs of a recursive feature elimination algorithm?

I am a bit confused with understanding the parameter step of RFE and RFECV algorithms. This is how I run RFECV for multi-class classification problem (3 classes): <...
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0answers
34 views

Calibrating probabilities of a binary classifier when class prior is unknown

Is it possible to calibrate the probabilities of a binary classifier when the class priors are unknown? In cases where the data is obtained with selection bias (i.e. more positives than negatives in ...
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0answers
12 views

Should oversampling/undersampling be applied only during CV or also for final model creation?

I am dealing with a highly class imbalanced dataset and am going to try oversampling and see how my nested CV is affected when comparing algorithms. When it comes to model finalization, should I ...
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1answer
22 views

Predict Based on Prediction?

I am working on a binary classification task with a pretty straightforward input set of numeric features. One of these features is particularly good, but it cannot be used in real life because it's a ...
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0answers
22 views

Principal component analysis for variable reduction

In the textbook “Principal Component Analysis” Jolliffe (§9.2) suggests the following method for variable reduction: “When the variables fall into well-defined clusters, there will be one high-...
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1answer
23 views

Minimum set of features that can distinguish all items [closed]

My input is a set of objects having different values with respect to a set of features: The output should be a set of minimal features allowing to distinguish all these objects or at least most of ...
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0answers
23 views

Trouble replicating sklearn logistic regression outputs

I am trying to create my own logistic regression classifier using scipy.optimize but I am having trouble getting close to the output of sklearn's built in logistic regression function. I am testing it ...
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0answers
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Suggestions required from experts for performance improvement for a binary classification problem using timing data

I am a currently working on location verification using machine learning and neural network techniques. This is a classification problem where the system has to classify whether a user (based on his ...