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.

Filter by
Sorted by
Tagged with
0 votes
0 answers
16 views

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
  • 1
0 votes
0 answers
32 views

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
  • 1
0 votes
0 answers
24 views

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
  • 188
0 votes
0 answers
15 views

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
0 votes
0 answers
30 views

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
  • 1
0 votes
0 answers
31 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
0 votes
0 answers
7 views

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
0 votes
0 answers
7 views

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
0 votes
0 answers
13 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
  • 149
1 vote
1 answer
71 views

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
0 votes
0 answers
22 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
0 votes
0 answers
22 views

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
  • 1
1 vote
2 answers
60 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
  • 11
0 votes
1 answer
30 views

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
0 votes
1 answer
27 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
  • 15
0 votes
0 answers
20 views

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
0 votes
0 answers
12 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
  • 1
1 vote
0 answers
37 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
0 votes
0 answers
15 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
32 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
  • 101
0 votes
2 answers
407 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
164 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
  • 173
0 votes
0 answers
88 views

LSTM multivariate time-series with categorical, numerical and non-temporal inputs

I have a dataset that contains different data types and I'm working on a prediction task of dataset features with LSTM network, but I'm struggling in finding the right way to construct the neural ...
luciadep's user avatar
0 votes
0 answers
114 views

Ordinal logistic regression prediction and accuracy using statsmodels

I am trying to do a ordinal logistic regression analysis using statsmodels. However, the predictions I'm getting are vastly different from that I get when using SciKit-Learn ...
antikbd's user avatar
  • 101
0 votes
0 answers
14 views

How to make a prediction if training time series have different lengths?

Description: I have 100 products. For each item I have the number of hours it has been used for each quarter of multiple years. Item 2020_Q1 2020_Q2 2020_Q3 2020_Q4 2021_Q1 2021_Q2 2021_Q3 2021_Q4 ...
Federico Gentile's user avatar
0 votes
1 answer
283 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
  • 188
0 votes
0 answers
14 views

How can I use a predicted machine algorithm model to find specific inputs?

I am relatively new to machine learning and now I am working on my thesis regarding that! My goal is to find a prediction model to see if the strain of the three zones is similar to each other or not. ...
Javad's user avatar
  • 1
0 votes
0 answers
16 views

how to analyze model performance without any ML libraries using a BI tool?

I have a dataset that has the ML model predictions along with the true labels column of the predictions and ...
Adem Youssef's user avatar
0 votes
0 answers
38 views

How to interpret predictions from a specific PyTorch Model

I have obtained the prediction values from this PyTorch model, at least I think so(https://github.com/allegro/allRank) by running: slates_X, slates_y = __rank_slates(val_dl, model) But the output ...
Tartaglia's user avatar
  • 101
0 votes
0 answers
35 views

LSTM model constantly underpredicts

I have a dataset that consists of temperature measurements. The temperature is increasing as time goes by. I have developed different RNN models (LSTM,BiLSTM,GRU,BiGRU) to predict future values of ...
Maria Pantopoulou's user avatar
0 votes
0 answers
15 views

Appropriate sample size for prediction algorithm

Our study aims to develop a Random Forest algorithm to predict the incidence of suicidal thoughts, after one year, based on the responses given to four surveys at baseline (time-1). Each survey ...
Andre's user avatar
  • 1
0 votes
1 answer
22 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
  • 617
0 votes
0 answers
35 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
0 answers
7 views

Understanding RSV in WrapCauchy

I am trying to predict using wrapcauchy. This was the best fit when running the fit_transform() method. Unfortunately, I am running into some issues. I keep receiving the error: ...
isabella's user avatar
0 votes
1 answer
58 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
  • 153
0 votes
1 answer
37 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
  • 1
0 votes
0 answers
21 views

Tensorflow prediction of (PRNG) future values

I would appreciate if you could help me with the following problem: Future values of a given time series of pseudo-random values should be predicted. It is unclear how good the PRNG performs and if it ...
iaksyrc's user avatar
0 votes
0 answers
9 views

Should we reinsert trend after doing forecast using detrended data?

Basically, when we detrend a signal, we detect and remove a linear component of that signal. This produces a stationary version of that signal. And we can use various forecasting algorithms to ...
Enes Kuz's user avatar
0 votes
0 answers
22 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
  • 101
0 votes
1 answer
451 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
0 answers
13 views

Consumption rate on a small dataset with variability

I am looking to find the consumption rate, or how fast I am consuming energy so that I can later predict when my energy will reach a certain threshold. My dataset is fairly small and looking to see ...
Lynn's user avatar
  • 101
0 votes
0 answers
36 views

Robustness of an ARIMA Model

I have built an ARIMAX model in python for predicting a time series. After presenting my findings ive been asked what robustness tests i have used. My skillset is more on the python side. I only have ...
DVCITIS's user avatar
  • 131
0 votes
1 answer
34 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
28 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
0 votes
0 answers
102 views

How to deal with multiple and overlapping timeseries from weather prediction/forecasts in pytorch-forecasting?

Dear Data Science community, I want to run temporal fusion transformer supposed by google research. Meanwhile it is part of pytorch-forecasting and I want to setup a ...
dl.meteo's user avatar
  • 111
1 vote
0 answers
35 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
0 votes
0 answers
11 views

Help in creating a prediction function for linear regression model

Hi i need some help to create a prediction function for a Multiple Linear Regression model. This is the collab file Please help Collab File I am confused how to apply transformation on the data and ...
Utkarsh Singh's user avatar
0 votes
0 answers
21 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
  • 1

1
2 3 4 5
10