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# 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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23 views

### Probablistic Assumption on Linear Regression

I am reading Stanford CS229's lecture notes online and on page 16 (page 17 in PDF page identification) and I am stuck on understanding a good portion of the page. For the context, we assume that the ...
8 views

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### Can I train a logistic regression model for combining ML models to form an ensemble?

I have 3 ML models trained to perform classification on a dataset. I want to combine them into an ensemble model. I understand that there are multiple ways to do this - voting classifier, stacking, ...
1 vote
40 views

### Fitting users' reports with joint time-semantic model

I have a historical list of reports, made by users, containing what happened (taken from a list) and the time when the report was filed. And I would like to fit the data with some joint time-semantics ...
14 views

### How to get probability of an outcome from skewed t distribution in R

I am trying to calculate the probability of stock return to be greater than X in next 28 days, using the skewed t-distribution as it fits the best to the ...
24 views

### Generating a Sample T-Distribution in Python

I'm new to DataScience. I'm going through the stats module and the ways to create a sample T-distribution. Using the below line to generate the sample. However, my question is how is the array ...
20 views

### Intuition behind this bayesian probability?

Original Question - Prevalence of a disease X is 0.1%. You take a test for this disease and it turns out positive. This test is 99% accurate. What is the probability of you having the disease given ...
25 views

### Probabilistic line of best fit

I have data about pedestrian counts from multiple sensors along a street. I know the location of each sensor. Assume that the street has total length L. I want a function F(l,t) that gives pedestrian ...
14 views

### Can an OCR model consistently recognize every digit of a long number correctly?

I'm working on OCR on scanned documents and we need to recognize the exact sequence of some printed numbers on it. Imagine you're reading a bank cheque serial number (16 digits) so the system needs to ...
57 views

### Getting actions probabilities instead of an unique prediction in Stable Baselines 3 SAC?

I try to understand how getting an actions probability table instead of an unique prediction in stable baselines 3 SAC in order to override 'predict' method to filter invalid actions. I guess the good ...
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17 views

### Inverse Probability Fallacy of Maximum Likelihood Estimation

How can we justify that the parameters estimated via Maximum Likelihood Estimation are the optimal parameters for the data, given that MLE involves computing the data's likelihood as a function of the ...
21 views

### Is using Probability Classification to predict whether a restaurant will purchase the best approach?

I have a data set that contains data about restaurants in the United states including menu, foot traffic, type of cuisine, type of restaurant, and other restaurant attributes. I also have a small ...
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### If a set of random vectors are independent then would the join event of the random vector from the set and another random variable independent?

If all x_i from i=1 to n are independent. And y_i is dependent on x_i. Then can we always say that all (x_i, y_i) tuples are always independent of each other? x_i is a random vector of shape mx1, y_i ...
20 views

### $p(f|X,Y) \propto p(Y|X,f)p(f)$

I'm reading a paper where it mentions Gaussian processes, the author defines a prior distribution over function space $p(f)$ and states the following about the posterior $p(f|X,Y) \propto p(Y|X,f)p(f)$...
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285 views

### Negative Log Likelihood of a Gaussian Model can be negative?

I am confused about the negative log likelihood of a guassian model: Can the negative likelihood of a gaussian model be negative ? lets suppose that the variance is going to 0 faster than the MSE ...
1 vote
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### Probability Distributions

I was going thru a course on probability and probability distributions for data science and in that they were describing the various probability distributions with mathematical formulae. I was ...
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### Reinforcement Learning: Formally, does an exponentially decaying epsilon satisfy GLIE?

I am aware that exponentially decaying exploration constants (epsilon) are used practically. Formally, though, do they satisfy the GLIE condition? Specifically, relating this to the Borel-Cantelli ...
43 views

### What does maximize average log probability mean?

In the word2vec paper (https://arxiv.org/pdf/1310.4546.pdf) that introduces the skip-gram algorithm we encounter this phrase: which says that we maximize the average log probability. Can someone help ...
18 views

### Conditional density estimation for sequences using conditional random fields

I am looking to estimate the conditional distribution of the next observation $x_{t+1} \in \mathbb{R}_+$ of a discrete-time process, given the current observation and $l$ previous observations. I am ...
30 views

### Check the validity of the distribution in the proof of No-Free-Lunch Theorem

I'm reading the proof of No-Free-Lunch Theorem (quoted at the end of this question) in Understanding Machine Learning: From Theory to Algorithms, Cambridge University Press, p.37, the author wrote: ...
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### Is probabilities mean of predicted class (RandomForest) a consistent estimator of class recall?

I'm working on a classification problem in order to predict among 50 different classes. I'm using a Random Forest classifier and I'm using the predict_proba method ...
152 views

### Hi, I need help with this question. This quesion is based on Markov Chains. I want to answer it without using any simulation

Alinah is spending the summer at her grandparents’ farm in a small town in Iowa. The town is known for frequent changes in its weather. Each day starts off as either sunny or rainy. There’s a 50% ...
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1 vote
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### Do models of social systems suffer from prediction drift?

Background I've created a binary classification model that predicts the probability of fraud for a given sample. The choice of threshold allows me to set how many frauds are captured in the training ...
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1 vote
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### Trying to extrapolate info from a partial data set - statistical inference

I am wondering if my logic is OK here or not. 98% of a group without a device has an event occur 2% of group with device has an event occur Since we know that correlation isn't causation I can't say ...
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1 vote
44 views

### probability distribution

Just wanted to know if the value we get by passing, say, random.normal(shape=(3,2)) in the Tensorflow, etc, are normally distributed or if they are randomly chosen ...
1 vote
363 views

### Precision vs probability

Say I have a model which predicts a class $C_i$ from an input $X$, with a probability of 0.95 i.e $P(C_i| X)=0.95$. That would mean that if we do this over and over, then 95/100 times we would be ...
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### Predicting probability of reaching a milestone -- How much data should I use from production universe to train/test model?

If I am predicting probability of a business to reach (x) milestone (classification 1), but the only data I have is live production data, how much of the production data should I use to train the ...
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### Get dependant probabilities in multiclassification

After training my CatBoostClassifier model I call get_proba function which returns me list of probabilities. The problem starts from an another point... I transfer that data into dataframe then to ...
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### How to demonstrate two variables are orthogonal with respect to the output in a 3-D Python dataset?

I have a Python dataset with 300 samples and 3 columns: 2 independent integer variables X,Y and the dependent continuous variable ...
1 vote
109 views

### Calculationg perplexity (in natural language processing) manually

I am trying to understand Perplexity within Natural Language Processing as a metric more fully. And I am doing so by creating manual examples to understand all the component parts. Is the following ...
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1 vote
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### whats the difference between these two value function definisions?

I've seen in literature two different yet similar approaches when writing the value function in an MDP: \$V_\pi(s)=\sum\limits_{a\in A}\pi(a|s)\sum\limits_{s'\in S}\sum\limits_{r\in R} Pr[s',r|s,a][r+\...
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### Good models for predicting whether a customer would make a purchase given details like age, gender, ethnicity, salary, etc?

I have around 30,000 data points and for those data points I have some numerical fields like customer_age, ...
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### Practical example of difference between p(y|x) and p(x|y)

I've been reading about the difference between generative models and discriminative models. I know that for generative models we learn the joint probability p(x,y) or just p(x|y) and p(y). For a new ...
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### How is Probability Used in Data Science? [closed]

This is my first Question so apologies if I do not stick to the standards. What I want to understand is how is all of the following topics: Probability Different Probability Distributions. Baye's ...
1 vote
145 views

### Mathematically rigorous NLP

I'm looking for resources (books/articles/whatever) that provide mathematical formalization of NLP and statistical language theory. By that I mean clear exposition of the subject in terms of ...
1 vote
69 views

### Strategy to choose maximum value from an unknown array of n numbers

Suppose you have an array of n normally distributed numbers whose values are initially unknown(and the probability parameters are unknown too). You must choose one number and you want it to have ...
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214 views

### Compute the pdf from pandas kde

I have data (features/targets in machine learning terminology), e.g. X1(t), X2(t), ... XN(t) and dependent variable y(t). I can use pandas to plot the kde's of the independent variables (X1(t),...). I ...
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105 views

### How can I obtain the mean of a Poisson distribution given the first improbable point of the distribution?

I generated a Poisson distribution with mean equal to 3 and 10000 samples by using np.random.poisson(3,10000). The plot is the following: from this plot I see that ...
1 vote
100 views

### Probability for Nth Place in Race from Bradley-Terry Model Inputs and Outputs

I have created a motorcycle race prediction model that is given pairs of racers and outputs the probability of each rider beating the other in each pairwise comparison. That info is then processed ...
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### Bayesian state description in Reinforcement Learning

What's the best approach to feed a bayesian description of an observed state to a Reinforcement Learning agent? Brief context: I have an agent situated in an environment, which it perceives through a ...
86 views

### How does factoring probability distributions help?

I'm trying to make sense of machine learning and am reading Deep Learning by Goodfellow, Bengio and Courville. In section 3.14 they show an example of factoring a distribution then say "These ...
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612 views

### Threshold tuning with one-vs-rest for multi classification python

I’m currently using a One vs Rest Random forest algorithm for multi class classification problem using Python, and I want to find the optimal threshold for each class, How can I do this with OVR (One-...
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13 views

### approximating probability mass function from a large data

I am learning elementary probability; especially I am interested in learning how to find probability mass functions and density functions from data. I think I perfectly understand the theory: For ...
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1 vote