Questions tagged [binary]

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19 views

Binary classification problem with imbalanced dataset, how to compare to random classifier

We have a very imbalanced dataset (2% of class 1). To the best of our knowledge, there is no baseline in the literature to the problem we want to solve - so we thought of comparing our performance to ...
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11 views

how to generate variates from a particular categorical binary data?

So im working with more than 100 thousand samples dota2 dataset which consist of the winner and the "hero" composition from each match. I was trying to build winner of the match prediction model ...
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34 views

How do I read a dat file, for which I don't know its structure?

Is there any way to atleast read the text from the dat file. I have its corresponding mdf file hence I know what all data and columns are there in it. How do I figure out the contents in my dat file. ...
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1answer
28 views

Predicting the next occurrence based on binary

I have no experience in statistics or machine learning. I have a True/False binary array describing occupation of open public spaces ...
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2answers
21 views

Does it make sense to train multiple classifiers for multiple partitions of data?

Let's say I have a dataset consisting of 100 features and a binary target variable. On exploring the data, I see that Feature 10 which is binary, seems to split the data in an 80:20 ratio with respect ...
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1answer
32 views

Using Majority Class to Predict Minority Class

Suppose I want to train a binary model in order to predict the probability of who will buy a personal loan and in the dataset only 5 percent of the examples are people who marked as bought a personal ...
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1answer
38 views

Binary Clasification Accurary

newbie speaking: Commonly we can say that accuracy is defined as total positive/ total nbr cases. But I read that, when it is a binary classifier we should consider: TP+TN/ total nbr cases. Can ...
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2answers
19 views

If in t-SNE digaram of binary classification both classes follow the similar curve what does t-SNE diagram show?

If in t-SNE digaram of binary classification both classes follow the similar curve what does t-SNE diagram show for instance: Figure1 or Figure2
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44 views

undersampling problem in imblanced dataset ValueError: Unknown label type: 'continuous'

I would like to undersampling the data but I encounter the following error? ...
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3answers
58 views

What is the best metric to evaluate highly imbalanaced binary classifiction? (such as fraud detection in credit card)

What is the best metric to evaluate highly imbalanaced binary classifiction? (such as fraud detection in credit card? I have examining several metrics precision recall F1 lassification Report (macro ...
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1answer
32 views

Data Science Take Home Challenge Interpretation of Question

I am currently applying for a Data Science position and have to finish a take-home challenge for one of the companies. However, I don't really understand what they want me to do and hope you can help ...
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2answers
84 views

Training model on a Balanced vs Imbalanced dataset?

Let's say that I have a 2-class classification problem where classes A & B have 10*N and ...
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1answer
1k views

How to interpret classification report of scikit-learn?

As you can see, it is about a binary classification with linearSVC. The class 1 has a higher precision than class 0 (+7%), but class 0 has a higher recall than class 1 (+11%). How would you interpret ...
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0answers
9 views

How to use “related” and “unrelated” as classes rather than multiple classes?

I have a dataset with about 15 feature columns and about 1000 rows that I'd like to use for supervised training. Every row can be classified as "related" or "unrelated" to another row. About fifteen ...
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19 views

Learning discrete probability distribution that is parametrized by a set of real-valued parameters

Assume I have a discrete probability distribution defined over binary variables. This probability distribution is parametrized by a set of real-valued parameters, which all are contained in a segment, ...
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0answers
8 views

Suitable aggregating method for condensing sets of binary values into a single real one

I have a dataset composed of several subjects. Each subject has a series of binary indicators where 1 indicates that a the subject presents an indicator and 0 means that the indicator is not present. ...
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1answer
88 views

Impose similar metric on segments to model

I am training a binary classifier in a dataset using AUC as a score. The dataset has two main groups (we will refer to them as good and bad population). A property that this dataset has is having a ...
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0answers
34 views

Indicator for target variable in logistic regression

I am trying to predict the probability of an event occurrence for different entities based on historical time series data. The event is binary (0, 1) and monthly snapshots are available. I am setting ...
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2answers
576 views

Binary classfication vs One-class classification

Why do we need samples of both classes for the training of binary classification algorithms, if one-class algorithms can do the job with only samples from one class? I know that one-class algorithms (...
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0answers
15 views

Is there a way to choose obtain an optimal threshold to maximise F1 measure using ROC?

I am trying to choose the best threshold for a binary classification problem that maximises F1 measure. Currently, I am manually calculating the F1 measure at thresholds 0.1-0.9 in steps of 0.1. I am ...
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1answer
26 views

CNN for checking existance of single label

i am just thinking about training a neural network which uses data of only one single label. For example: Assuming i have many images which contain a dog. Now i want to teach the network how a dog ...
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31 views

Looking for an alternative for prefix codes like Huffman coding, how to code empty space efficiently without prefix codes?

I'm experimenting with some coding mechanics using prime numbers and quantum mechanics. My problem is that those are no more prefix codes and I'm lacking of ideas on how to encode empty space between ...
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2answers
1k views

Binary encoding and its interpretation in Python

I have a column named Street that has 2 values: Paved and Gravel. Here is what print(train[binary_columns[0]].unique().tolist())...
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4answers
102 views

Is it OK to train a binary classifier using all the extremely imbalanced data if the majority class is negative?

I'm training a neural network as a binary classifier for text classification. The data is very imbalanced, where the ratio of TRUE:FALSE is approximately 100:10000 Intuitively, it feels like using ...
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0answers
15 views

Perpendicularity between random variables?

I am reading Bechavod et al. (2017) [1], and at page 3 there is written: In the example, each data point lies in $X = (X_1,X_2) = \{0, 1\}^2$ and has two features—$X_1 = A$ is the protected ...
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0answers
75 views

Cluster method with binary variable

I need to do a cluster analysis for the following variables: ...
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1answer
24 views

Forcing class imbalance to mirror the target data

I'm trying to do binary classification on some data, my source data has a class split of 40% A / 60% B while my target data has a split of 70% A / 30% B. Is it a worthwhile strategy to use SMOTE to ...
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1answer
48 views

Anomaly Detection System

I need a sanity check. I want to create an anomaly detection system. The logic which I am planning to use is the following: Find anomalies in the past using Seasonal Hybrid Extreme Studentized ...
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2answers
82 views

Deep Learning for high contrast images with small differences

I am trying to make a deep learning classification on the gear part you can see in the images. The contrast is high and almost binary. I want to classify the images where the circle located closest to ...
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0answers
1k views

Binary Classification of Numeric Sequences with Keras and LSTMs

I'm attempting to use a sequence of numbers (of fixed length) in order to predict a binary output (either 1 or 0) using Keras and a recurrent neural network. Each training example/sequence has 10 ...
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1answer
2k views

Micro-F1 and Macro-F1 are equal in binary classification and I don't know why

I have a binary classification problem which in the test set, the number of data in both classes are equal (the test number of class 0 and class 1 are equal). Since we know that the number of samples ...
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0answers
29 views

Correct approach to usage of class labels in cell imaging data

As part of a group project at university, we are given a series of videos of cell cultures over a 24 hour period. A number of these cells (the "knockout" cells) have had a particular gene removed, ...
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1answer
53 views

Which Loss function is correct for binary mapping?

I have built a 3 layer neural network to perform a binary mapping (2016 inputs, 288 outputs.) I am getting decent results with mean square error and stochastic gradient decent. My question is: Is ...
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2answers
721 views

Using neural network for “features matching” binary classification

We have a dataset of numerical features from two images and we want to check if these images match or not using only these features. Basically we have have these columns: fA1, fA2, ..., fA14: 14 ...
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1answer
21 views

Optimal proportion between the amount of Class = 1 and the amount of Class = 0?

I am quite new machine learning methods, so I may not write proper technical formulas. My question is about the optimal proportion between sample size in Class = 1 ...
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1answer
35 views

How to include class features to linear SVM

I am planning to do a simple classification with a linear SVM. One feature I have is another classification of some sort done previously. Can I just use this class feature as a 1-hot encoded array? So,...
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1answer
137 views

Binary Classification without machine learning tools

I have to write a binary classifier for my company that should be as simple as possible and doesn't use machine learning libraries (and I also should not code too sophisticated algorithms by myself). ...
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1answer
64 views

Binary classificaiton for weather data if its class 1 or class 0 alert

I am working on weather data and it has few features that are independent variables such as severity, severity_id, ...
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2answers
45 views

How to detect influence on behavior

From a behavioral study data was extracted. The study was about how people change their eating behavior, following visual cues. There were to groups of people: One was shown visual cues and then it ...
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0answers
913 views

Candidate Elimination Algorithm - Simple Problem

I'm trying to understand version space learning and the Candidate Elimination algorithm. Define the set of most general and the set of most specific hypotheses. Take these training examples with the ...
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1answer
37 views

Unintuitive results when Expanding Binary Classification to Multiclass

I have aproblem where I need to predict when a Truck arrives to pickup something. Say we have formulated that a binary classification model, where 0: The truck coming for pickup today 1:The ...
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1answer
235 views

Binary (Unary) Recommendation System with Biased Views

I would like to create a content recommendation system based on binary click data that also takes views into account. What content a user has been exposed to, and therefore has the chance to click ...
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1answer
46 views

What Kernel is suitable for the following data for SVM classification?

I have the following 2 class data, as shown below. . Its a hand crafted example using two ellipse equations. I want to know what might be a recommended kernel to be used with this problem if I want ...
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1answer
127 views

Significant overfitting with CV

I working on a binary classification task. The dataset is quite small ~1800 rows and ~60 columns. There are no duplicates in the rows. I am comparing different classifiers amongst the canonical ones: ...
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2answers
393 views

Data binning - Why we need to transform Categorical Variables?

Having a lot of categorical features and other numerics why we need to transform the categorical to binary values? Is it for using the values in mathematics functions of the algorithms? Thanks!
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1answer
38 views

Binning which variables?

I will try to implement a k-means algorithm over this dataset: ...
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0answers
763 views

Backpropagation with step or threshold activation function

I understand that gradient descent is local and it deals only with the inputs to the neuron, what it outputs and what it should output. In all I've seen, gradient descent needs the activation function ...
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1answer
235 views

decision rules for each feature (binary classification)

I have a collection of 10 features (all numerical) and a single binary outcome variable. I need to train a binary classification model, find the best features and compute thresholds for each feature. ...
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2answers
180 views

How to create an ensemble that gives precedence to a specific classifier

Suppose that in a binary classification task, I have separate classifiers A, B, and C. If I ...
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3answers
112 views

adding logic combinations of boolean features in classification

I want to build a classifier from a dataset of vectors that include exclusively boolean values. Is there any chances that my classifier might perform better if, previously to the learning, I add ...