Questions tagged [binary]

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79 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
25 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 ...
2
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2answers
84 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
9 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 analysing the F1 measure at thresholds 0.1-0.9 in steps of 0.1. I am ...
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1answer
12 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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0answers
13 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
278 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
44 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 ...
1
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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
54 views

Cluster method with binary variable

I need to do a cluster analysis for the following variables: ...
0
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1answer
19 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 ...
1
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1answer
32 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
43 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 ...
1
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0answers
814 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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0answers
31 views

Need help understanding time series approach used for predicting earthquake arrival?

In predicting the arrival time of earthquakes, a paper here seems to make use of a time series approach that is making me scratch my head, and I would appreciate any guidance on understanding it. In ...
2
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1answer
1k 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 ...
2
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0answers
28 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, ...
1
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1answer
52 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 ...
2
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2answers
507 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
19 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 ...
2
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1answer
31 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,...
1
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1answer
82 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). ...
0
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1answer
51 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, urgency_id etc ... Based on these values, I would like to classify alerts into class ...
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2answers
44 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
667 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
33 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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0answers
142 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 ...
1
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1answer
45 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 ...
3
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1answer
116 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
183 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
32 views

Binning which variables?

I will try to implement a k-means algorithm over this dataset: ...
2
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0answers
602 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 ...
1
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1answer
197 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. ...
2
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2answers
156 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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1answer
70 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 ...
3
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1answer
2k views

Binary classification toy problem

I'm trying to build a toy model which can identify a constant difference between two variables: (if variable1- variable2>10 then 1 else 0). This should be a ...
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0answers
77 views

Transforming multiclass problem into binary problem to improve accuracy

I found a code for a classifier for a 6 class problem where the classes are integers from 0 to 5. I found this code that I tested and it improved my accuracy highly. Can anyone explain the spirit ...
1
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1answer
2k views

Sklearn Aggregating Multiple Fitted Models Into A Single Model? (binary classification)

My problem context: dataset too big to fit into memory. binary classification [0,1] 30 csv files in a directory with exactly 30,000 samples (rows) each file contains 15,000 ...
0
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1answer
690 views

Binary predication from binary variables

Logistic Regression generates a binary outcome for a non-binary variable. I need a binary outcome from a binary variable. This is the requirement. How to predict binary A using previous values of A?...
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0answers
57 views

Why is my predicted vs observed plot worse for training than validation. Running an overfitted GBM on a binomial outcome

I have a binomial outcome that I am trying to predict using a gbm in h2o. I have set quite a low min_rows value for each node and it appears to be overfitting. See plots below. When I group the ...
0
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1answer
519 views

Binary classification of partially labeled data

One of my friends was asked this question in an interview. A clue/restriction is given: Do NOT use semi-supervised learning techniques. Suppose you have a binary classification problem: There are ~...
23
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3answers
8k views

Best practices to store Python machine learning models

What are the best practices to save, store, and share machine learning models? In Python, we generally store the binary representation of the model, using pickle or joblib. Models, in my case, can be ...
0
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1answer
2k views

How do I pick “K” for precision at K and recall at K?

I understand precision at k and recall at k. It is a more useful metric for evaluating the success of a binary classifier when the positive class is overwhelmingly out-weighed by the negative class. ...
0
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1answer
162 views

Why predicted proababilities from this binary classifier does not sum up to 1?

I have a C5.0 model that is trained to predict binary class (C1/C2) on a dataset with 20 features. The model is configured to perform boosting (10 trials) and it has a ...
0
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1answer
169 views

Failure tolerant factor coding

There are a lot of ml-algorithms which cannot directly deal with categorical variables. A very common solution is to apply binary (dummy-) coding to still properly handle the categorical nature of ...
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0answers
1k views

How to quantize weights in forward pass during training in Keras?

In Keras, I'd like to train a network with binary weights in the manner of Coubariaux, et al., but I can't figure out where the quantization (binarization) should occur within the code. A core aspect ...
2
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2answers
11k views

Is a correlation matrix meaningful for a binary classification task?

When examining my dataset with a binary target (y) variable I wonder if a correlation matrix is useful to determine predictive power of each variable. My predictors (X) contain some numeric and some ...
2
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2answers
397 views

Cluster very many sparse binary vectors

I have a very big set of high-dimensional, but sparse binary vectors. Each vector represents a "one-hot-style" n-gram sequence of words where each index of the words that occur in the n-gram is set to ...
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0answers
79 views

binary longitudinal time series

What kind of feature engineering techniques should one apply for longitudinal data comprising of individual binary time interval data about when an activity was done during the day(we have this data ...
7
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2answers
1k views

Why are precision and recall used in the F1 score, rather than precision and NPV?

In binary classification problems it seems the F1 score is often used as a performance measure. As far as I've understood the idea is to find the best tradeoff between precision and recall. The ...