Questions tagged [probability]

Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur or how likely it is that a proposition is true.

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What algorithms can handle probabilistic targets?

I have a classification problem where I want to want to use probabilities instead of classes to train my model to learn to output probabilities. In my dataset, I have instances where the probabilities ...
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How to prevent underflow when calculating probabilities with the Naïve Bayes Classifier algorithm? [closed]

I'm working on a Naïve Bayes Classifier algorithm for my data-mining course, however I'm having an underflow problem when calculating the probabilities. The particular data set has ~305 attributes, so ...
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Combining multiple probabilities from a classifier. Propagating probabilities

Let's say I have trained a classifier that classifies images of animals into 10 different classes. And let's say that I have 20 different images of a particular animal and because I know the ...
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28 views

Designing a network for multiclass regression

I'd like to model a continuous conditional probability distribution for two classes on a given data set. eg the height of men and women from a set of inputs. I can train a regression model (DNN, CNN, ...
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9 views

Distance between two time-dependent distribution

In my research, I want to use a meaningful and computationally tractable distance between two time-dependent probability distributions. For stationary distributions, several distance measures are used,...
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1answer
29 views

Creating a training dataset from analytical solution

I am currently redesigning an inverse problem on an experimental technique, but I am having doubts about how to create a training dataset. Here is the problem I am trying to solve: I have already ...
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Ensemble of different reservoirs (echo state networks)

Suppose I want to do reservoir computing to classify the input to the proper category (e.g. recognizing a handwritten letter). Ideally, after training a single reservoir and testing it, there would be ...
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Calculating classification metrics when “true” label is also generated by another classification model

I have a binary classification model $A$ and want to calculate its precision and recall for positive and negative classes. The "ground truth" or "true" labels for this model are ...
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different scored probability distributions for a classification model using python vs Azure ML Studio

I have a classification model which I initially built in Azure ML studio and then created a similar model in python (its similar because the algorithms in python VS Azure are a bit different so they ...
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Interpreting the results of the probabilistic neural networks (Monte Carlo dropout approach)

I have a Keras NN model where I apply the Monte Carlo dropout approach as a predictive method to evaluate the uncertainty of the model outputs. From my research in the probabilistic neural networks, I ...
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Error term in probabilistic interpretation of least squares update rule

I have read in Stanford's CS229 course notes that to justify the least-squares update rule with probability, the following is assumed: $$y^{(i)} = \theta^Tx^{(i)}+\epsilon^{(i)}$$ , where $\epsilon^{(...
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1answer
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Compare cross validation values of Bernoulli NB and Multinomial NB

I'm testing the Multinomial NB and Bernoulli NB on my dataset and I'm using the cross validation score to better understand which of the two algorithms work better. This is the first classifier: ...
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1answer
46 views

How to implement conditional probability distribution on set-valued Random variables

I'm trying to implement conditional probability distribution when the events of two RVs are sets. If I try to extrapolate concepts from real or categorical variables to sets things become confusing ...
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26 views

How to set seed for random drawings with Numpy? [closed]

I'm trying to set the seed for a few lines of code in a jupyter notebook. However, when I tried running numpy.random.seed(0) in the initial cell, in the later cells the random generator was not '...
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Neural Network probabilities problem

I am using machine learnig to measure probability for the outcome of tennis matches. If the winer is 1 that means that p1 won otherwise p2 won. in Columns LG, SVC, RF and NN there are probaiblities ...
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Classifier Performance - Binomial proportion confidence interval

I am solving a binary classification task. As an output of Random Forest classifier, I get a probability of how sure RF is that class is 0 or a 1. How can I calculate the needed threshold, to be 95% ...
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1answer
34 views

What is a distribution-wise asymmetric measure?

I was trying to understand KL-Divergence, $$D_{KL} \langle P(X) \Vert P(Y) \rangle,$$ and was going through its Wikipedia article. It says the following In contrast to variation of information, it is ...
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1answer
28 views

Which probability distribution will you use to model outliers?

I was asked this question in a recent interview for the position of a Data Scientist: Which probability distribution will you use to model outliers ? I told him outliers are like rare events which ...
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1answer
36 views

R code that gives results like Wolfram Alpha for the expectation of a function of a random variable? [closed]

When I ask Wolfram Alpha to calculate $E[f(X)]$ where $f(x) = e^{-x^2}$ and $X \sim \mathcal{N}(1,4)$, it gives the result $$ E[f(X)] = \frac{1}{3\sqrt[9]{e}} \approx 0.29828, $$ and the following ...
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how to interpret this 'lift chart'? prediction and true labels

i am trying to compare the prediction from my classifcation model and it's true label either 0 or 1. ...
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1answer
23 views

What is the most common practice of generating (X,Y) from an arbitrary CDF or PDF?

So I can generate X from arbitrary CDF F(x) by the procedure above. Can it be generalized to two variables? How, exactly? If not, what's the best way to generate <...
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19 views

Tensorflow Model not returning a Distribution object when having DistributionLambda as last layer in a multitasking model

I am building a TF CNN model that takes a picture as input and has 3 outputs (multitask learning). On one of the output layers, I would like to output a distribution object, ...
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Learn smoothly varying mean and variance of a variable over a 2d domain

For a problem which I am working on at the moment, I'm interested in learning how the mean and variance of some response variable y changes with two independent ...
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2answers
27 views

How to generate a random sample and distribute values based in an probability distribution?

I want to generate a random sample based on this probability distribution: The line is the KDE of the histogram. My random sample will have n values, the value is ...
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17 views

How to find a probability distribution the parameters of which do not impact each other like mean and variance in normal distribution do?

I need to find a probability distribution to fit my data. My data has two important features, duration and activity count. Duration means how long one sequence lasts and activity count means the ...
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1answer
68 views

What is the difference between maximum likelihood hypothesis and maximum a posteriori hypothesis?

I am a student and I am studying machine learning. I am focusing on the concept of Bayesian learning and I have studied the maximum likelihood hypothesis and the maximum a posteriori hypothesis. I ...
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26 views

Separation of two probabilistic distribution: gaussian and exponential

I have a dataset where I highly suspect some correlation by two variables, based on my understanding of the problem. I would have a linear correlation (sort of SVD decomposition or a plane such as $y=...
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What is Probability Fusion on this figure?

I'm reading the paper Few-Shot Semantic Segmentation with Prototype Learning. I have tried to reach the authors, but they don't answer my emails, so I have decided to ask my question here because I ...
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1answer
88 views

Problem understanding probabilistic generative models for classification

I am a student and I am studying machine learning. I am focusing on probabilistic generative models for classification and I am having some troubles understanding this topic. In the slide of my ...
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1answer
70 views

Naive Bayes Denominator clarification

I came across an earlier post that was resolved and had a follow up to it but I couldn't comment because my reputation is under 50. Essentially I am interested in calculating the denominator in Naive ...
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2answers
66 views

How to predict when an appointment will be scheduled?

I have a dataset of tens of thousands of appointments. Appointments have a created date and scheduled date. Something like this: ...
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1answer
47 views

Probability of an event [closed]

How should I go about solving the following problem? If you randomly type a 6-digit number on a note, what is the probability that you can see the same number if you flip your note upside down? How ...
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1answer
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Train a model to determine that the probability of an event given a set of features is higher than when given a different set of features [closed]

I have a data set of attempted phone calls. I have a set of features, say, hour of day, and zip code. I have a label indicating whether the callee picked up the phone or not. I want a model to predict ...
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27 views

How do you calculate the probability that a certain number of hyper-parameter combinations contains the optimum combination?

How do you calculate the probability that a certain number of hyper-parameter combinations contains the optimum combination? Side Note: After doing more research, I have decided that Randomized Search ...
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1answer
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How to understand Bionomial Theroem and the Recursion Rule?

In this video from EDX, the instructor explains the binomial theorem as: Binomial Theorem: When you calculate $(a + b)^n = a^n + C(1)a^{(n-1)b} + C(2)a^{(n-2)b^2} + ... + C(n-1)ab^{(n-1) + b^n}$ The ...
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Calculating probability from a distribution

I have a histogram/count plots of average time a property is in the market. Given this distribution, I'd like to calculate the probability that a similar property will be leased within 'x # of weeks' ...
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1answer
30 views

Wrong result when solving: “chance that two random cards differ in color and value?”

I'm trying to build a simulation for this question: "There are 50 cards of 5 different colors. Each color has cards numbered between 1 to 10. You pick 2 cards at random. What is the probability ...
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1answer
57 views

How can i tell if my model is overfitting from the distribution of predicted probabilities?

all, i am training light gradient boosting and have used all of the necessary parameters to help in over fitting.i plot the predicted probabilities (i..e probabililty has cancer) distribution from the ...
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2answers
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How to model user choice probability: binary model vs multi class model

Let's say Morpheus has multiple users to offer colored pills(from an infinite set of colored pills), there are in total 3 unique colored pills(red, blue, green) Morpheus can offer. The trick is, ...
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1answer
57 views

why does my calibration curve for platts and isotonic have less points than my uncalibrated model?

i train a model using grid search then i use the best parameters from this to define my chosen model. ...
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1answer
26 views

What probability distribution would be more appropriate for monthly rate of going to the store?

Part of a model I am making includes the frequency with which people go shopping for a given good (e.g. people on average go to the supermarket some n times a month). I am trying to figure out what ...
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2answers
32 views

how classification scores are interpreted?

I would like to know how to interpret classification scores (i am not sure about the word score or probability, please correct me). For example, for a binary classification positive values are ...
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1answer
56 views

Stacked Model performance?

I am currently working with a dataset that seems very easily separable and I have an accuracy of 99% for SVM (NN-98%, RF-98%, DT-96-97% and I have checked for leakage & overfitting). As part of my ...
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using logistic:binary as objective in xgboost

i am using 'binary:logisitic' as my objective function in xgboost classifier. Therefore when i predict probabilities i.e: model.predict_proba(x_test)[:, 1] will ...
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2answers
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Lower loss always better for Probabilistic loss functions?

I am working on an neural net int Tensorflow that predicts percentages for win, draw, loss for given data of a game. The labels I provide are always {1, 0, 0}, {0, 1, 0} or {0, 0, 1}. After some ...
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how can i plot probability distribution of my classes in the way below?

All, I would like to plot the following: I have a binary classification problem where I am using xgboost as my 'model' below: ...
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1answer
18 views

how can i interpret kernel density plots from classification?

all, i have a classification problem where i am predicting likelihood of client defaulting on loan. i plotted the predicted probabilities from my model, and then plotted against the label '1' for ...
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64 views

Evaluation of Mixture Density Networks

I have programmed an Mixture Density Network model to a market price. As input I have many numerical and categorical properties. The output of the network is a probability distribution (shape, ...
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1answer
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Understanding output probabilites of xgboost in multiclass problems

I would like to understand the output probabilities of a xgboost classifier (or any other decision tree ensemble based classifier) in the case of a multiclass problem. For example: We have 5 different ...

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