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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14 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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30 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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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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78 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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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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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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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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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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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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How do I measure the magnitude of change of probabilities and also what exactly do these probabilities represent?

I am trying to optimize the strategy to choose while taking a penalty kick. I have identified two strategies- keeper independent and keeper dependent and I am trying to find the best one using a ...
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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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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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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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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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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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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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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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38 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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30 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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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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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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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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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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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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31 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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Relation between optimal value function and optimal action value function

In equation 3.17 of Sutton and Barto's book: $$q_*(s, a)=\mathbb{E}[R_{t+1} + \gamma v_*(S_{t+1}) \mid S_t = s, A_t = a]$$ $G_{t+1}$ here have been replaced with $v_*(S_{t+1})$, but no reason has ...
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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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28 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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How to compare ensemble spread with RMSE in order to find data points not included in the interpolation region?

I am currently working on the refinement of a huge dataset. The concept is that I want to reduce as many training data as possible. I have generated more than 1 million data without labels. To give ...
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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?

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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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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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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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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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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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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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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Estimate machine count for API dependency

I have a SDK, with many APIs, which is used by many apps. Those apps are installed on many machines. I get data containing machine Id, app name and API info . The data is sampled such that 2% of the ...
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“Smearing” probabilities or how to handle imprecise locations for canonically classification-type problems

I am trying to predict failures at different nodes on a line. Each node has different weather features and hardware/configuration features. For a little under half of the historical failures I have, I ...
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Regressor to estimate probability from samples

What is a good way to estimate probabilities in a dataset of samples? Each sample is a measurement, that is usually 1 or 0. The goal is to calculate probabilies based on all feature rows. Simple ...
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How to calculate Probability from MSE results?

I am using a MSE classifier to classify some binary images into 4 classes, I extract 8 dimensional features for classification and normalize them to the max feature of them, so the max value for any ...
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29 views

Clarifying Probability Mass Function (PMF)

I am currently reading Deep Learning book, and I want to get better understanding of probability theory. In chapter 3.3.1 of Deep Learning book it states that: Often we associate each random ...
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24 views

How to perform link prediction in text based relationship data

I need to establish if there is a link between 2 columns from two different datasets with one matching column, where; ...
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48 views

Convolution and Pooling as Infinitely strong priors

I am currently reading about Convolutional Neural Networks in Deep Learning Book. I am stuck on section 9.4 titled "Convolution and Pooling as Infinitely String Priors". Could someone please ...
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147 views

How to compute denominator in Naive Bayes?

Suppose we have class C_k and input feature vector x in dataset How to calculate probability ...
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Practical example and working of Laplace Smoothing or Linear Interpolation in Natural Language Processing (NLP)

Let us suppose we have a document where total_words = 50 (for example -> is,the,now,is,am,here,now) total_unique_words = 40 (for example -> is,the,am,here,now) How can we apply the ...
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Understanding these probabilities, and reading the pdf and cdf

UPDATE: this is a math question but as i would like to codify it, I thought the DS SE might be appropriate. I am trying to sketch out this problem statement. Where am I going wrong since I don't see ...

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