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Questions tagged [prediction]

prediction is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.

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Techniques for solving the problem with an unbalanced data set

I am trying to solve a problem with an unbalanced data set. I have two classes, one is for patients with risk (1), the other for patients without risk (0). I have a larger number of patients without ...
Naty's user avatar
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Calculating prediction confidence from a sequence of token-level confidences

I am working with OCSR (optical chemical structure recognition) models, and they output a sequence of token-level confidences. I am looking for a method of summarising these token-level confidences ...
finlay morrison's user avatar
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saving ML models with pickle to be deployed using Flask

I trained some ensemble Ml to predict, I needed to save with pickle so as to be able to deploy using Flask. To save with pickle I have tried several methods and read several articles but could not get ...
Kehinde Olatunji's user avatar
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Build a Neural Network for Multi-output Regression

I have a network model that accepts about 25 inputs and outputs 3 actions. The outputs are: delta X and delta Y of the robot and the angle of the robot. After I enter the data into the model, I get ...
May's user avatar
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1 answer
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Missing data in train set and test set

I have a dataset of N columns. Now I'm able to preprocess data and find a subset of features that I can use to train a model and make predictions. In the case where the train data has missing feature ...
0-0's user avatar
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Machine Learning Algorithm for identifying the factors contributing to academic performance of students

I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/...
Dawood Ahmad's user avatar
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Some questions about Ensemble batch prediction intervals (EnbPI) algorithm

On line 18, should j not start with t-s+1 and end with t? On line 19 why is the same x_t considered in the loop?
user1156715's user avatar
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Creating a rule based approach to identify Stock Out products

I am trying to build a Stock Out Predictive Model based on input variables such as: Sell In Unit: Units per month sold to wholesaler by manufacturer Sell Out Unit: Units per month sold by wholesaler ...
Sushmoy Mallik's user avatar
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is Sequences, Time Series and Prediction course up to date?

Recently I asked a question regarding Time series prediction and someone commented that I should consider taking DeepLearning.AI course: Sequences, Time Series and Prediction. My goal is to make good ...
Cohensius's user avatar
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40 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 ...
GerardL's user avatar
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Why is my NN model's prediciton for y= sinc(x) function showing symmetric?

...
RimaMonica's user avatar
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Sale Forecasting Problem -- Is it legit to use inventory level as a feature?

I'm working on a project to predict future sales for our company's products so that the supply chain can have better idea how much to restock. Detail about the model I'm working on: Model: LGBM (from ...
user159479's user avatar
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Prediction with optional parameters

I want to build a machine learning model that has 25 input feature and two labels (my problem is a regression task if it makes any difference), to my knowledge since I have two labels I need two ...
Aws rayyan's user avatar
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26 views

Using simple RNN to identify a simple dynamic linear system

I have been trying to identify a simple linear second order system (e.g. a pendulum or a mass-spring system), by simulating it in Python using backwards-euler method and then feeding the step changes ...
APasagic's user avatar
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16 views

R, Caret Predict(), and errors

So I've been playing around with/testing out a few ideas. I just wasn't sure though if there is a simple command you can use to have caret like send you back a list (or data.frame) of all the errors ...
Nevermnd's user avatar
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seasonal adjustment to testset

I would like to understand how to apply a seasonal adjustment to my testset. Let's imagine we have a time series and divide it into trainigset (80% of the samples) and testset (20% of the samples). I ...
Cata's user avatar
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Winter Holt's Time series model

I am confused with the Winter Holt's Time series model usage. I use 2 years of data to train and want to predict 3rd-year data. Note1: I have partial 3rd year's data, but I want to use it to check my ...
kg__'s user avatar
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Prediction of Quarterly Financial Numbers

The task is to predict the quarterly revenue numbers using machine learning. Only 28 quarterly data points for financial numbers are available as companies release the revenue data quarterly. I have ...
Kriti's user avatar
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Can a multivariate MIMO LSTM forecaster learn the relationships between the multiple feature outputs?

Question: Can a multivariate MIMO LSTM learn the relationships between the multiple feature outputs? This question arose when I decided to modify a multivariate (Multiple Input - Single Output, MISO) ...
Zezimabig's user avatar
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Calculate the curve of a list and apply that to calculate the values of a larger list

I have a list of ~125 sorted ascending values and I am converting those to percentages of total so that they add up to 100% (shortened example would be: 0%, 0%, 15%, 15%, 30%, 40% with the total of ...
Disz's user avatar
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167 views

Prediction of the next number 0 to 9 that doesn't have a particular sequence

How to predict a number from 0 to 9 that are random and doesn't have any particular sequence that the numbers are following?
user155498's user avatar
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Creating insights from Battery monitoring parameters (State-of-charge, battery cell voltages, temperature, etc.) to use with AI or model based

So, in a new role currently and I decided to pursue the health monitoring and impending failures of batteries (Lithium Iron Phosphate, Lithium Ion and a few lead-acid as well) but having never done it ...
Ameer Usman's user avatar
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Dynamic dosing recipe for accurate pH

I want to have a script for adjusting dosage of ingredients in each batch dynamically. Assuming that the requirement is to have a specific value of pH from each batch but with the variation of raw ...
Pittoon Hanvivatpong's user avatar
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15 views

Finding/analyzing data competitions that share the individual model's predicted outcomes?

I would like to analyze past machine-learning data competitions, focusing on bias and variance of predictions. I thought I could look at past kaggle competitions, but unfortunately kaggle typically ...
Matifou's user avatar
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1 answer
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Dealing with varying predictive horizon

I know that the predictive horizon is the time window that runs from the observation of the data to the manifestation of the target variable. But how can I deal with prediction if the time horizon ...
Marco Ballerini's user avatar
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23 views

accuracy on test set is always close to the distribution of label

here is a time series, at each time $i,$ we have several features $(a_1, a_2, ... a_k)$ and a binary label $y.$ Now I use a window $$(a_1[i], a_1[i-1],..., a_1[i-s],..., a_k[i], a_k[i-1],..., a_k[i-s])...
user6703592's user avatar
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What Can Prevent Time-Series Prediction Model From Learning Trend?

I am building an encoder-decoder prediction model based on this paper: https://www.sciencedirect.com/science/article/pii/S0952197623001483 It is made of a transformer encoder and a 1D CNN Decoder. The ...
LaTate's user avatar
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1 vote
2 answers
109 views

Feature selection - How to identify the best subset

I am using three feature selection method on a dataset containing 15 inputs. I need to extract the best 5 features. Each of the three method gave a subset of the input dataset, but they are different. ...
Aparna's user avatar
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1 answer
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What is the highest possible prediction accuracy when I flip some labels at random?

I want to predict MNIST labels in a binary setting using a simple MLP model (0 for digits 0-4 and 1 for 5-9). For the train and test data, I randomly flip 25% of the labels. Is the maximum achievable ...
Johannes97's user avatar
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1 answer
90 views

Do prediction intervals for Random Forest predictions are average of prediction intervals of trees being Random Forest estimators?

I am working on adding prediction intervals for each prediction value of new input samples. Do prediction intervals for Random Forest predictions are average of prediction intervals of trees being ...
Paulina's user avatar
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After training an LSTM model using log returns as the input and obtaining a binary output of either 0 or 1, how can I predict stock movement?

I have been working on a personal project called "Predicting Stock Movement using LSTM." For my project, I have selected log returns as the input (X) and the target (y) is whether today's ...
Murtuza's user avatar
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0 answers
13 views

Large Language model for regression on urls

I am trying to fit a BERT model for a URL regression task. I have a URL as a feature and I have to predict a metric M for it. Keeping a learning rate like $10^{-5}$, the model is overfitting in about ...
guesta's user avatar
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1 vote
0 answers
39 views

ML with Python - extract information from user text

I'm a web developer, got a little experience with Python but none on ML. Tour operator customer want to introduce AI/ML on his website, the goal is to have a single text input where user can prompt ...
fudo's user avatar
  • 111
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0 answers
16 views

Classifying a set of time series with restrictions on the classes

I have $N$ time series, each having $T$ time points, with the class of each time series known. There are $K$ different classes. I want to predict the classes for a set of $M$ time series (with time ...
ArunavB's user avatar
0 votes
1 answer
48 views

Sequence prediction in Parent - Child dataset

We have a large collection of documents (D), each accompanied by a set of metadata (M). Within this collection, some documents act as parent documents and have multiple child documents. Both parent ...
6nagi9's user avatar
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0 votes
2 answers
872 views

How to predicting the next date with Python ML

I have a list of dates around 10 dates in asc order. These are the dates a buidling was open. I need to predict the next date using this. I tried scikit learn like below ...
RandString's user avatar
1 vote
1 answer
175 views

How to predict what someone will order?

Suppose Prof. X goes to a road side tea-coffee shop everyday at 5pm just after his office. After reaching there he tosses a coin, and places his order tea or coffee. The shop owner Y has been ...
S. M.'s user avatar
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1 answer
456 views

Remove Seasonality before applying SARIMA model on weekly data?

I am trying to predict average weekly stock prices for time series data. Steps I followed: I tested the data to check whether it was stationary or not using ADF ...
Kriti's user avatar
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0 votes
1 answer
29 views

Integrating time context in a machine learning model

Basically, what I'm curious about, are there any methods in machine learning to make the model take into account events that happen in real time that affect the data points during that time period. ...
Maxim Chopivskyy's user avatar
0 votes
1 answer
16 views

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 ...
Connor's user avatar
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0 answers
44 views

Differential equations, real time measurements of variables, and ML

TL;DR: We measure variable $x$ every $10$ minutes, solve a differential equation $\frac{\mathrm{d}y}{\mathrm{d}t}$ where $y=f(x)$. We are interested in the time it takes for the cumulative value of $y$...
Hitanshu Sachania's user avatar
0 votes
1 answer
85 views

Testing RANSAC regression model

I am going to build the model (e.g. multiple linear regression) to predict the appartment cost in my city. First I have to find outliers in training data. For this task RANSAC regression algorithm ...
Irina Svist's user avatar
0 votes
1 answer
20 views

Force network to weigh specific variables during learning

I have a pandas data frame containing around 100000 observations of plant species and their age with additional numerical predictors (climate). I used tensorflow ...
kjtheron's user avatar
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0 votes
1 answer
40 views

Combine machine learning feature selection with time series

I have basic knowledge in time series prediction and supervised/unsupervised machine learning algorithms (clustering, classification, decision tree, etc.) I am now given a task to predict a bunch of ...
Alex's user avatar
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0 votes
0 answers
24 views

How to improve pytorch network to be more precise

I have a pytorch neural network which is being trained on data containing multiple financial values and some other non numeric values translated to numbers with self created logic (for example if ...
Mi Ro's user avatar
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0 votes
1 answer
620 views

Append prediction of tensorflow to a pandas dataframe

I built a tensorflow model to make text classification in four category, after testing and evaluating it, I need to apply it to actual data to predict the class of them, I create a predict function ...
Ali A. Jalil's user avatar
0 votes
1 answer
37 views

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 ...
Master_Sniffer's user avatar
0 votes
1 answer
29 views

Excessive features in an Neural Network model

I am modeling a quality parameter of a chemical process product. I have a list of circa 400 process parameters sampled throughout the process. Most of them should have no meaningful impact on the ...
machinelearner's user avatar
1 vote
0 answers
42 views

How to improve the AUC scores of my link prediction algorithm?

I am exploring a link prediction algorithm, but my AUC scores change every time I run it and it is always very low. It varies from 50 to around 72. I was wondering if there is a way to improve their ...
OSCAR CONTRERAS's user avatar
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0 answers
22 views

Predicting number of women who will give birth on a given day?

I have a set of data with information about women and their expected delivery dates for childbirth. I have more columns in the table but for simplicity let's just focus on the below and assume that my ...
Tom's user avatar
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