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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36 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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21 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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13 views

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
27 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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25 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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25 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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Probability that 2 samples have the same datapoints

I have been thinking about this question for a few days now and I don't know how I could approach this probability problem. Let's say I'm building a random forest model with 50 trees and with a total ...
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16 views

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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13 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
24 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
35 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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25 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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12 views

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
84 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
53 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
59 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
38 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
33 views

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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16 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
24 views

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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13 views

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
54 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
122 views

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
34 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
29 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
43 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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16 views

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
38 views

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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31 views

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
15 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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54 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
52 views

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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15 views

non-deep learning alternatives to mixture density network

I am currently using a Mixture density network to fit a distribution to a large dataset. The input to my network contains many features, while the output is a simple one-dimensional probability ...
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1answer
42 views

Probability of Gaussian Naive Bayes

How would I go about attaching a probability to the prediction outputted by a Gaussian Naive Bayes model ? I'm asking because the predict_proba function U can use with sklearn's Gaussian Naive Bayes ...
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2answers
20 views

Notation for features (general notation for continuous and discrete random variables)

I'm looking for the right notation for features from different types. Let us say that my samples as $m$ features that can be modeled with $X_1,...,X_m$. The features Don't share the same distribution (...
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1answer
85 views

What is the concept of Normalized Mutual Information in the evaluation of Clustering?

I know what mutual information basically is but not quite sure about why and how it is used in the context of evaluation of clustering mechanisms ? Can someone please explain the intuition behind it ? ...
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1answer
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Finding gender affinity for businesses

What are the different models I can use to find the gender affinity of businesses using yelp dataset-- https://www.kaggle.com/yelp-dataset/yelp-dataset . I need to find Probablity (Male buying from a ...
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How do data scientists reason under ambiguity? [closed]

I am looking for real-wrold examples of how data scientists build models and make decisions under situations of extreme ambiguity as described by Cassie Kozyrkov here: A decision under ambiguity ...
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1answer
196 views

Fitting a pandas dataframe to a Poisson Distribution

I have a simple dataframe df2 that consist of indices and one column of values. I want to fit this dataframe to a poisson distribution. Below is the code I am using: ...
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12 views

How to calculate probability of a users belonging to a single group over time?

Please bear with me, I am new to statistics and data science. I am trying to do a customer segmentation based on multiple features I am continually collecting on each customer over time. I expect ...
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1answer
64 views

how to compute bernoulli entropy?

I am reading gail implementation code in openai baselines. they compute bernoulli entropy as one of the loss in adversary network loss function. In their code, they implement bernoulli entropy as ...
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2answers
79 views

why we sample when predicting with Recurent Neural Network

I trained a Recurrent Neural Network to predict the next word in a sentence. I trained and now I want to predict, but there is something I am not getting well. I saw it in many tutorials even in the ...
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7 views

Validating periods in a time series

i'm currently looking for an algorithm which is capable of solving the following task: A time series of discrete values (i.e., counts of crimes) is evenly spaced among 365 days. My task is to find ...
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17 views

Ranking graph's nodes by score propagation

Problem I have the following directed tripartite graph $G(E\cup V\cup P, A)$, where there is a many-to-one symmetric relationship between the subsets V and E - $e\in E,v\in V,[e, v]\in A \iff [v, e]\...

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