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Questions tagged [classification]

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

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6 views

Capsule networks for binary classification not training brain images classification

Currently I am trying to implement a capsule network using Xifeng Guo's Keras code for capsule nets. I have a dataset of brain tumor images with 98 negatively labeled instances and 155 positively ...
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Classification Algorithms For Noisy Problems

Dear fellow data scientists I work in finance and have decent experience with neuronal networks. Right now I am facing a challenge where I need to classify a set of signals. The data set looks ...
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Naive Bayes / SVM classifiation - min. number of records (Python)

I am doing text classification with Python. I have around 120 records with 2 columns: text class I tokenize, stem and lematize the words, I also did some of my own text preprocessing. When I run the ...
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Big difference in randomTree accuracy with train and test sets

I've created a model using randomForest for the following dataset: https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice The thing i'm questioning is that the results of the model when ...
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Should features be correlated on uncorrelated for classification and regression (prediction)

I have seen researchers using pearson's correlation coefficient to find out the relevant features -- to keep the features that have a high correlation value with the target. The physical implication ...
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How can I determine best performing groups in a series

Not sure if this is right place for this question, but taking an example of the following trend, how can I determine that groups A and B are the areas where the result has been best? I have already ...
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23 views

Managing NaN in target variables (testing)

Please can someone advise me on how to handle NaN in my target variables set? I've tried a variety of things but none is working. Here's what I've tried: Imputing zeros (0) in Y_test Replacing NaN ...
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Can feature representation acquired by a same model but trained on different corpus be used on the same classification model?

For example, if I wanna do document classification with doc2vec embeddings, first I train the training set to get doc2vec embeddings, and fit the embeddings to a classification model; later on when I ...
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1answer
21 views

Cocktail party problem ICA

I'm trying to solve the cocktail party problem (Independent Component Analysis) in a real application. So let's say there are two speakers and two microphones. What I'd to know is if it's mandatory ...
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1answer
24 views

Detect if my ANN model is overfitted

I've been trying the kaggle dataset of Credit card fraud detection Dataset . I've used ANN using keras and tensorflow. You can find the code in the screenshot. The only problem is im getting accuracy ...
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2answers
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Text classification for data with multiple labels per observation

I have a dataset of tweets that has been labeled by multiple people. So the columns look something like: Tweet_ID, Coder_1_Classification, Coder_2_Classification, etc. The idea is to build a tweet ...
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Detection of UI Elements using CV

I have a task to detect UI elements in the photo of the touchscreen. I did several decisions based on the research that I did, but I am no very confident with them so I would appreciate feedback on my ...
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How to predict unordered dictionary in the output? [on hold]

I have (key,value) pairs coming from a dictionary that the model has to output. There can be 50 or more of these (key,value) pairs in single dictionary. The dictionary is unordered which means whether ...
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Tensorflow classification - maximize the accuracy of certain classes

I'm doing some experimentation and trying to train a forex trading model to classify based on three classes: Buy Sell No action Input rows are labeled as buy when ...
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2answers
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Why are ROC curves better for imbalanced datasets?

I have recently read this: " AUC(Area Under Curve) is good for classification problems with a class imbalance. Suppose the task is to detect dementia from speech, and 99% of people don’t have ...
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1answer
24 views

Relating ROC curves with class statistics

I have three neural net models that I am running on the same dataset (of 7 classes) and calculate their class performance and also ROC curves. The firs tmodel is a 4-layer model with 8 neurons in each ...
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1answer
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should i use clustering or classification [closed]

I have a dataset that has dates and then I extracted some features out of them. Now, I want to play around. Columns: time_for_task_a: end date - start date for task (a) time_for_task_b: end date - ...
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Random crop in multi-label image classification context

In some research papers, people use random cropping with variable sizes and then they resize them to original size as a data augmentation technique saying that it helps boost results. Can someone help ...
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1answer
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Large amount of Sigmoid outputs are ones and zeros

I have Keras neural network for binary classification with final layer having one output with Sigmoid activation. I have noticed that large amount of output numbers are strictly one or zero (rather ...
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What is the best method to implement a real time fraud detection model for ATM or POS transaction? [closed]

I am seeking for suggestion what best technique of data mining should I use to model a real time fraud detection system on ATM and POS transactions based on the customer's past transaction history. ...
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1answer
24 views

Evaluation method for multi-class classification problem modeled as binary classification problem

I should mention that even though I have some basic knowledge regarding ML, it is the first big ML project I am working on and for the proposal of my research project I need to suggest an evaluation ...
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1answer
16 views

Time Series Classification for 1 hour blocks

I am doing some analysis on time series. The time series would consist of 3 channels and contain 5 minute interval data. What I want is to be able to give it a 1 hour block of 5 minute interval data ...
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1answer
31 views

Maybe wrong values for precision and recall

I'm trying to do some data mining with RapidMiner studio. I've applied the K-nearest neighbor algorithm with different values of K. As I expected, accuracy increase and after K=5, it decrease. But I ...
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Deep Learning for Video Classification

Which Deep Learning architecture is best for classifying short videos of variable length? I would like to classify videos that last from 1 up to 3 seconds.
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1answer
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Classification - Divide the interval (0 - 1] to lets say 100 classes and use each class to make a calculation

class-1 represents 0.01, class-i represents 0.01*i, class-100 represents 1.00. Thus, when the classifier predicts the class-y and it should have predicted class-(y+1) there is a small error so we can ...
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1answer
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Covariates in machine learning classificatoin

I would like to classify a number of people as sick and healthy. I have all the body measures as features. I have to control for age and sex because body features are affected by that. How do I adjust ...
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Classifying points exactly on decision boundary

For calculating loss arose by classification we do this: If $y (w \cdot x + b) > 0$: $\text{no loss}$ If $y (w \cdot x + b) < 0$: $\text{loss} = −y (w \cdot x + b)$ So here what about the ...
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1answer
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Analysis of sales performance

This is my first question on this stackexchange - i hope i'm in the right place and i'm asking the right question. I work for a business, we sell certain products. We are running a trial currently on ...
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1answer
27 views

classifier predicts only one class [closed]

I have a classification that has to predict three different classes: gcc,icc, clang. The prblem is that if I use a blind test set to do a submission, when I look athe the prediction I have on it I ...
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2answers
38 views

K fold cross validation reduces accuracy

I am working on a machine learning classifier and when I arrive at the moment of dividing my data into training set and test set Iwant to confron two different approches. In one approch I just split ...
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1answer
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How to update the posterior belief when we are observing a stream of correlated data from a fixed but unknown data source

I want to build a [probabilistic] model that aims to infer the true value of an unknown categorical variable, $y \in \{1,2,..., K\}$. We have a dataset $(X,y): \mathbb{R}^d\rightarrow \{1,2,..., K\}$ ...
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Data Augmentation techniques for classification of imbalanced time series datasets

Now I have a task to classify the imbalanced time series datasets using ML classifiers, such as Logistic Regression, Decision Tree, SVM, and KNN. I am not allowed to use the Deep Learning tools, such ...
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1answer
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How can different classification algorithms expressed as neural networks?

I have heard that each of the different classification algorithms can be expressed as a neural network architecture. How can the different algorithms like Logistic Regression, SVM(Support Vector ...
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How to define quadratic weighted kappa as eval_metric in catboost classifier

I am using catboost for a multiclass classification problem. I want to use quadratic weighted kappa as the evaluation metric. Catboost already has WKappa as an eval_metric but it is linearly weighted ...
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How to Implement the 1D minimization problem in SDCA (Stochastic Dual Coordinate Ascent) Algorithm

I am trying to implement the SDCA algorithm and the pseudocode is shown in the image below. My question is how to solve the 1D minimization problem. I am using a logistic loss function with the usual ...
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21 views

Multi-class classification with custom loss matrix?

Suppose I have classes A,B,C and some predictors. I want to minimize the loss function where the loss penalties are arbitrary penalties applied to each possible misclassification e.g.: $$L = \begin{...
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problem submitting classification problem

I am trying to make a submission, so I have a test set without labels and I am tryin to test my classification model on it. In particular, I have also to submit this prediction as a csv. I have the ...
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1answer
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Classification: Dealing with unknown class balance in the prediction dataset

I'm working on a classification problem that predicts if a grant application will be accepted. The data I'm training on is from 2005 to 2008. I'de like to predict any time after 2008. The issue I'm ...
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1answer
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help finding research discussion on HTS classification

My question is about the theory of this problem, and not necessarily syntax. I'm wondering if anyone here has experience with automating HTS (Harmonized Tax Schedule) classifications, specifically ...
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3answers
47 views

One hot encoding for multiple label(trainy) in .fit() method?

I have a mobile price classification dataset in which I have 20 features and one target variable called price_range. I need to classify mobile prices as low, medium, high, very high. I have applied a ...
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DL classification loss lowers but doesn't go to zero

I'm trying to train a text classifier using pytorch and the model currently uses pretrained embeddings, a bi-lstm followed by a linear layer and dropout. When I start training the loss is at 60-70, ...
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Deep learning model performance for splitted datasets?

I'm new to machine learning.... I want classify the heart beats extracted from an ECG using machine learning, I have built ANN with an input layer, two hidden layers, one with 200 and the other one ...
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questions about the positive predictive value from a classifier output

[This is in the context of machine learning applied to drug discovery.] Suppose you have trained a classifier with a set of chemical compounds of known active $(A)$ vs inactive $(I)$ class. The model ...
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1answer
47 views

Increase accuracy of classification problem [closed]

I am trying to build a classifier that predicts the compiler given some operations of assembly code. Here is the pandas dataframe: What I do is using a TfidfVectorizer and select the features that ...
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1answer
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Classifcation of non-linear regressions based on their shapes

I have a data set of thousands of individual y ~ x relationships that can have varying shapes in their relationships. For example, they can follow an exponential, asymptotic, logistic or hump-shaped (...
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2answers
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How to leverage description data in multi-class classification (dimensionality reduction)

I'm currently working with a dataset of 55k records and seven columns (one target variable), three of which are nominal categorical. The other three are 'description' fields with high cardinality, as ...
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1answer
28 views

Finding out which values lead Random tree to a decision

I have a dataset of machines that produce plastic parts. A camera evaluates whether a plastic part was produced correctly or not (binary classification). I'm trying to figure out which factors ...
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Binary classification of graph pairs

I have a dataset made of pairs of graphs and a binary label (0 or 1 depending on if the graphs are similar). I am trying to find a model that, when given two graphs, will output if these two graphs ...
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Time series forecasting dilemma. Could feature engineering overcome time dependency?

I keep reading articles about time series forecasting. They all start from the same assumption: time series forecasting can't be treated as a regression/classification problem. It is time dependent, ...
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1answer
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Comparing AUC, logloss and accuracy scores between models

I have the following evaluation metrics on the test set, after running 6 models for a binary classification problem: ...