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Questions tagged [binary]

The tag has no usage guidance.

1
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1answer
22 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
16 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 ...
1
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2answers
31 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 ...
1
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0answers
55 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 ...
0
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0answers
12 views

Combining features for explainable binary classification, imbalanced dataset with minimal manual checks

I'm building a binary classifier which should detect between "fake" and "genuine" objects for a certain domain. I have designed a dozen of numerical features which are typically large for fake objects,...
-1
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1answer
23 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 ...
1
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0answers
84 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
30 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
51 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: ...
0
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2answers
99 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!
0
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1answer
26 views

Binning which variables?

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

Modeling ideas for multi-stage process

This is more of a conceptual question: I am looking for some guidance on selecting an appropriate model to predict a binary outcome. A business tracks its individual sales through a number of stages. ...
2
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0answers
237 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
vote
1answer
96 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. ...
0
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0answers
29 views

Loss function that is robust to a shifting binary target

I'm trying to squeeze as much performance out of a very noisy data set as possible. Initially, I tried to predict a continuous variable, but my feature set performed no better than randomly chosen ...
2
votes
2answers
96 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 ...
1
vote
1answer
36 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 ...
4
votes
1answer
939 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 ...
1
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0answers
34 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
vote
1answer
925 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
395 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?...
0
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0answers
57 views

Multiple binary variable combination prediction

I have read about Logistic Regression and Multiple Logistic Regression, but I couldn't find an machine learning methodology that matches the following requirement. A,B,C,D,E are 5 binary variables. ...
1
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0answers
42 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
votes
1answer
260 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 ~...
8
votes
2answers
2k 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
votes
1answer
787 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
votes
1answer
133 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
votes
1answer
99 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 ...
1
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0answers
960 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 ...
1
vote
2answers
5k 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
votes
2answers
305 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 ...
1
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0answers
57 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 ...
5
votes
2answers
803 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 ...
2
votes
1answer
59 views

Predicting or patron find of a binary variable over time

I'm new to ML and trying to find some practical use to it I encountered with the chance of saving the connections and disconnections (the binary variable) of a bunch of users like this: "User A ...
1
vote
1answer
817 views

Binary Neural Network Classification or Multiclass Neural Network Classification?

I am confused about the difference between a binary and multiclass neural network classification. If I am writing an algorithm that has 2 output classes (Obama or Romney), but not yes or no (so not ...
5
votes
1answer
167 views

how can I generate a Bernoulli block mixture model in matlab?

I am trying to write the code of a Bernoulli block mixture model in matlab, but am facing an error every time I run the function. In particular, I'm having a problem with how to relate the ...
38
votes
8answers
12k views

How to deal with version control of large amounts of (binary) data

I am a PhD student of Geophysics and work with large amounts of image data (hundreds of GB, tens of thousands of files). I know svn and ...
10
votes
4answers
248 views

Why might several types of models give almost identical results?

I've been analyzing a data set of ~400k records and 9 variables The dependent variable is binary. I've fitted a logistic regression, a regression tree, a random forest, and a gradient boosted tree. ...
15
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5answers
14k views

Choose binary classification algorithm

I have a binary classification problem: Approximately 1000 samples in training set 10 attributes, including binary, numeric and categorical Which algorithm is the best choice for this type of ...
7
votes
1answer
227 views

Using SVM as a binary classifier, is the label for a data point chosen by consensus?

I'm learning Support Vector Machines, and I'm unable to understand how a class label is chosen for a data point in a binary classifier. Is it chosen by consensus with respect to the classification in ...