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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2answers
481 views

XGBoost outputs tend towards the extremes

I am currently using XGBoost for risk prediction, it seems to be doing a good job in the binary classification department but the probability outputs are way off. i.e., Changing the value of a ...
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1answer
117 views

Improve NER label results on Non-English text

I am working on some Medieval Latin text and was using various methods of NER such as CLTK (Latin Model), Spacy (Multilingual, Italian, Spanish Model) and StanfordNER (Spanish Model). When I used the ...
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1answer
109 views

Dealing with population instability

I am working on using machine learning to correctly predict a binary classification using an input dataset that I receive about once a month. The idea is that I train, test and validate the ...
5
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2answers
2k views

Clustering or classifing n-gram-based text categories

I have large set of data records looking like this: "text", "category" I extract n-grams from text (2-, 3- and 4-grams) and store count of each n-gram per ...
4
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2answers
58 views

Classifier that optimizes performance on only a subset of the data?

I'm working on machine learning problem where I'm only interested in getting high accuracy within a narrow band of my predicted likelihoods. Specifically, I want an algorithm that will score very ...
4
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3answers
94 views

How can we model the class which maximizes the event probability?

I’d like to ask about a case when we would like to predict the best class of some input variable, so that the probability of event will be maximized. For example the advertisement type for a given ...
4
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1answer
405 views

Using the Datumbox Machine Learning Framework for website classification - guidelines?

A short while ago, I came across this ML framework that has implemented several different algorithms ready for use. The site also provides a handy API that you can access with an API key. I have need ...
3
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0answers
26 views

Why don't Target/LeaveOneOut Encoders work well for Regression Tasks?

In this review of categorical encoding, it states early on that For regression tasks, Target and LeaveOneOut probably won’t work well and later repeats that Target/LeaveOneOut (Owen Zhang's ...
3
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1answer
82 views

Hyperopt vs Default Values

When I use the hyperopt library to tune my Random Forest classifier, I get the following results: Hyperopt estimated optimum {'max_depth': 10.0, 'n_estimators': 300.0} However, when I train the ...
3
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0answers
84 views

How to implement hierarchical labeling classification?

I am currently working on task of eCommerce product name classification, so I have categories and subcategories in product data. I noticed that using subcategories as labels delivers worse results (84%...
3
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0answers
486 views

How to train continuous/soft classification model?

The classic classification problem is like finding the function $F:\mathbb{R}^n\mapsto \{0,1\}$. The label set will be [Apple,Banana,Banana,...,Apple]. What if I want to train a function $F:\mathbb{R}...
3
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1answer
896 views

How to use one hot encoding of string categorical features in keras?

I am dealing with a binary classification problem. The output column of my dataset is already encoded in 0/1. The problem is that I have many categorical features (columns), which are strings and I ...
3
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0answers
157 views

Multivariate time Series classification - One class

I need your help with time series classification. I have measurements of different medical parameters for patients captured at every one hour. The output label is whether the patient has Acute Kidney ...
3
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1answer
106 views

Extract features from a survey

I need to use the answers from a questionnaire for training a classifier. I discovered that some questions can have nested sub-questions.. Let's say (just an example) that I want to predict whether a ...
3
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0answers
62 views

make prediction with a time serie

I want to build a model that can detect which driver is driving now the car based on a dataset that contains 20 driver records for 3600s each driver ( the dataset contains all the car sensors values ...
3
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1answer
385 views

Multi-task learning for Multi-label classification?

I have a multi-label classification problem wherein each example can belong to one of the pre-defined classes (or can belong to none of them). I was wondering if I can somehow apply multi-task ...
3
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1answer
48 views

Restrictions on my skewed validation data

I have a severely skewed data sets consisting of 20 something classes where the smallest class contains on the order of 1000 samples and the largest several millions. Regarding the validation data, ...
3
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1answer
1k views

Should we use discrete or continuous input for decision trees

I have 2 datasets, a continuous dataset(75 datapoints and 14 variables) and a discretized dataset which was made by placing the continuous datasets into buckets. I have built a decision tree ...
3
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0answers
5k views

Adding multilabel classifier to TensorFlow example

I am starting with the generic TensorFlow example. To classify my data I need to use multiple labels (ideally multiple softmax classifiers) on the final layer, ...
3
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1answer
156 views

Shifted feature distribution across different datasets

I am trying to validate a classifier using two different training and testing datasets. The feature I am considering is a feature constructed doing the fold-change between two original features, i.e. ...
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0answers
106 views

Using classification to find the best support and confidence measure in associative rule mining

I have been trying the find the best support and confidence values for associative rules mining. I came across the following approach from an answer on Quora - Picking the "appropriate" values for ...
3
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0answers
388 views

Illustrating the dimensionality reduction done by a classification or regression model

Tl;DR: You can predict something, but how do you explain the prediction? Your usual classification/regression setup Lets say the data is a classic regression/classification problem: several ...
3
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1answer
42 views

Which classification algorithms are negatively affected by class imbalances?

I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
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0answers
35 views

Why decision tree algorithm performs better in small dataset in compare to other classification algorithm?

I read in some paper that decision tree algorithms have better result in small dataset like(400-600 records) when compared to other classification algorithms like SVM, Naive Bayes and KNN. I want to ...
2
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1answer
48 views

How to justify the usage of 200 dimensions in word vectors instead of the 300 dimensions?

When employing machine learning methods in NLP, most of studies use 200 or 300 dimensional vectors. 300 dimensional embeddings carry more information and this, therefore, is considered to produce ...
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0answers
17 views

Scikit learn - best model to classify supervised two-feature data?

I'm quite new to scikit learn but I am looking for the best approach to go about classifying some data I've collected where each set contains two measurements made over several points of time, along ...
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0answers
16 views

Keras model with second to last sigmoid activated Conv1D layer followed by globalMaxPool outputs values outside [0,1]. Why?

I am trying to train a binary classifier. It is a residual network with skip layers etc. but ultimately, the bottom two layers are a 1D convolution with sigmoid activation followed by a global max ...
2
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1answer
95 views

How to correctly set a target for a time series based model?

I need help determining the best way to go about creating the target variable for a machine learning model that is trading a financial instrument (stocks, foreign currencies, crpyto, etc). Below is ...
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0answers
51 views

Neural network cost is constant never changing during training

I am trying to build a binary classifier to predict a pulsar star with Single Hidden layer Neural Network. But the cost on training dataset after almost 100 iterations has no change, following is the ...
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0answers
114 views

Target mean encoding worse than ordinal encoding with GBDT ( XGBoost, CatBoost )

I have a dataset of 23k rows of an unbalanced dataset 85/15 ratio, 10 variables ( 9 of which are categorical ) , i'm using CatBoost and XGBoost for a binary classification. I applied cv (5 iteration ...
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0answers
29 views

What is the current state-of-the-art video classification technique?

For a project I am aiming to automise the detection of goals in foosball (a.k.a. 'table football') matches. To do so I now track the ball in every frame using the openCV library in Python. To ...
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0answers
30 views

how to work with NLP with other features

My dataset looks like this ...
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0answers
33 views

Using deep-learning on graph data for binary classification

The data: I have certain data that I decided to represent it as a graph (I thought it would suit). So I have the weighted graph data that includes a numeric attribute for each node. (networkx graphs)....
2
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2answers
40 views

Probability vs recall for time series classification task

I am working on the time series classification task that focuses on predicting a fault. I framed the problem as a multi-step forecasting problem, where my goal is to predict to the class at ...
2
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1answer
45 views

Blind feature engineering

I received a dataset for analysis that had ~100 numeric columns with anonymous column names(X1, X2, X3, etc...) and asked to do a binary classification. My resulting classification algorithm using a ...
2
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0answers
270 views

Differences between class_weight and scale_pos weight in LightGBM

I have a very imbalanced dataset with the ratio of the positive samples to the negative samples being 1:496. The scoring metric is the f1 score and my desired model is LightGBM. I am using the sklearn ...
2
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0answers
16 views

Should I back-calculate soft labels (probabilities) of my training set when I use probabilistic classifiers?

I have 2 datasets (D1, D2) to train 2 models (M1, M2). M1 is a probabilistic classifier, which outputs soft labels (probabilities of a sample belonging to each class) for a binary classification ...
2
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1answer
45 views

TF-IDF vs TF for classification

Let's suppose that I have a dataset of 1000 documents. Each document is a restaurant review (so relatively short text) and it has labels {Negative, Indifferent, Positive}. Let's suppose that the ...
2
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1answer
61 views

How to Setup Multivariate Time Series Dataset for Classification

First post on StackExchange. I’m fairly new to ML, with about 1 year of experience so please pardon any ignorance or misuse of terms. I have a multivariate time series dataset where I would like to ...
2
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0answers
232 views

Adjust class weights due to class imbalance and class importance Multi class classification XGBoost

With respect to this question and the answer given by @Esmailian, Would anyone be able to let me know if Class B has a higher importance or the positive class ( i.e. it needs to have a higher ...
2
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1answer
115 views

Dealing with biased binary classifier

My training data is weighed heavier on the '1' class, with about a 4:6 ratio. This outputs a classifier that is of 82% accuracy with an emphasis on the '1' class, which makes sense. ...
2
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0answers
115 views

Audio files and their corresponding spectrograms for image classification process

Suppose I have a dataset of audio files that I have to use for whale sound classification. I am choosing the strategy of treating it as an image classification problem by using their corresponding ...
2
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1answer
60 views

Difference in model performance measures of train and test data sets

I am using CART classification technique by dividing a dataset into train and test sets. I have been using Mis-classification error, KS by rank ordering, AUC and Gini as MPMs(model performance ...
2
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0answers
215 views

Hierarchical classification with multi-class predictor for every parent node

Edit: It turned out that I had an error in my function to compute the combined probabilities (a typo that changed the behavior of my function quite a bit without giving me an error message). Without ...
2
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0answers
26 views

Multiclass classification problem with more prediction classes than real classes

Can I have a multiclass classification problem with more prediction classes than real classes? For example: I want to predict the channel the user is going to watch. The real classes are "user didn't ...
2
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0answers
36 views

What’s more appropriate for outlier detection? Classification or Regression?

I'm using PyTorch and i’m working on a data set where I only care about “outliers” from the norm. The data is comprised of long time series with gaussian distribution, while once in a while there is a ...
2
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0answers
45 views

Multi-class classification dataset structure

I have a question regarding how to setup a dataset for modeling. Let’s say I have a dataset representing which car a person will buy depending on some characteristics: The dependent variables would ...
2
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2answers
198 views

How to extract and classify data from a column in excel?

I have a column in an Excel sheet that contains a lot of data separated by || delimiters. The data can be classified to some classes like Entity, IFSC codes, ...
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2answers
22 views

How should multiclass classifier performance be measured when one type of error is preferred over another?

Sorry if this question has been asked before--I am having trouble searching this topic since I'm not sure of my wording. Say you have a classification problem where there are more than two labels ...
2
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1answer
105 views

Data splitting for a binary classification model

I'm trying to build a binary classification model that will tell who's going to buy the product and who's not. I've heard that splitting a dataset into two different subsets is a common way when you ...