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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Prediction based on predicted data

may I ask if anyone of you knows well references on the prediction method based on the predicted data? By prediction based on the predicted data, I mean for example I have constructed a predictive ...
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What correlation is considered to be big for linear regression predictors?

It is well known that if two linear regression predictors highly correlate, it is bad for our model, but which correlation is considered to be big? Is it 0.5,0.6,0.8,0.9..? I have tried to find out ...
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Good model to predict color of the button to maximize site conversion

For example, we have a big internet store and we have Add to card button which can be blue or green. We want to show blue button to people who buy more with blue button and show a green button to ...
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Running model.fit multiple times for an LSTM?

I have time-series histogram data from many separate machine runs (see this post for detail). I am working to train an LSTM in order to predict the final histogram in a machine run based on the past ...
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Forecasting for multiple (Irregular spaced) Timeseires with interdependence

I have already asked a simmilar question, but i thoguth that this was not phrased well and hence i am trying a new post were i ask a better question. Let me know if this is ok. Judging by some of the ...
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Find the Outlier

I have data that contains points (geo coordinates of a random planet, integer pairs) that represent places where land is definitely there. Here is an example with ...
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Random Forest Model Train, Save and Predict Later vs Train and Predict Right Away - Different Results

I tested two pieces of code and they delivered different results, which was quite unexpected. First piece of code is supposed to train models in a k-fold manner, preserve each one of these fitted ...
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Time Series Hyperparameter Tuning

My question is about the intuition for hyperparameter tuning of time series. In other models, like Linear or Logistic Regression there is labeled data and according to accuracy or precision, the ...
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Price Predition for Irregular spaced historic data of non independent Prices

I am a little unsure how to proceed. I am not an expert but on a decent intermediate level when it comes to regular Timeseries. Now i am faced with a problem that first seemed related, but is an ...
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Error with decision tree prediction

I write this script in R about decision tree. ...
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TensorFlow Lite for Microcontrollers: Predicting with missing values and categorical variables

I work on a project where sensor data have categorical variables and missing values. Preprocessing sensor data with, for example, tfp.sts.impute_missing_values and ...
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Train LSTM model with similar cyclic sequence

I am using keras LSTM to predict a seq2seq of 2 variables. I have test results for 50 subjects with ±20 tests per subject. the data is a 2 variable sequence with shape (101,2). as you can see, the ...
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Kernel dies or proses stuck when making LR prediction on dataframe using apply

I'm trying to making predictions with a simple model. model=LogisticRegression() model.fit(X_train,y_train) After fitting, i try to make predictions. A sample ...
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How to make predictions on unseen data with different cardinality using xgboost

I am training an XGBoost regression model on a feature set $X$ that includes a feature $x_k$ with high cardinality (~100). First, I am using one-hot-encoding to convert $x_k$ and then split the set ...
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How to make an DL model predict Correctly [closed]

So I trained a DL algorithm using Keras for Human Action Recognition. The model has an accuracy of about 85 percent and a loss of 0.3 something. The problem is that the model did not predict well on ...
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Which algorithm is best for predicting diseases if symptoms are given? [closed]

After Topic modelling through LDA, I get the following dataset as result. ...
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best prediction technique for small dataset

Whats the best way to predict till time value 40. Thanks! ...
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1answer
35 views

Working with three types of data: numeric (integer, floats), images, and text for prediction

So I have three types of data (in title) and am wondering how I can combine the data. The target is numeric (price). My idea is to perform feature extraction on both the images and text, which would ...
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191 views

Python xgboost predicting future events

This is related to this article: https://towardsdatascience.com/forecasting-of-periodic-events-with-ml-5081db493c46 I found it interesting and tried to replicate it, having as a result a xgboost ...
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141 views

How to predict a certain time span into the future with recurrent neural networks in Keras

I have the following code for time series predictions with RNNs and I would like to know whether for the testing I predict one day in advance: ...
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Multiple Linear Regression for House Price Prediction score is 0.28 [closed]

I am trying to make predictions using this dataset What I have done so far: Dropped the Administrative column Encoded the categorical data using ...
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selection of loss function to avoid overfitting by autoencoder in prediction a figure with a sharp rise

I have to select the loss function to avoid overfitting by autoencoder in prediction of this figure that has a sharp raise, I would like to find how to avoid overfitting by autoencoder in prediction a ...
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ML algorithms recommand of online/batch learning for classification, prediction( and targetfunction), dataset parameter and label (A, B, C, Label)

Currently i am in a project. I will receive processing data constantly online from CNC machine, which will be like a dataset with parameters and labels, for example [A,B,C,Label],like 1st picture. The ...
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50 views

Pattern recogniser library for C# programs

I'm a regular user of the StackOverflow forum, but as this question is about a recommendation for libraries, which is supported at StackOverflow, and as my question is about data science libraries, I'...
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Confusion matrix of 3*2

I would like to include confusion matrix in my research report. I have a binary classification problem. The positive class is further divided into two types for example: Real Positive and Obstruction ...
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1answer
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How does an RNN differ from a CBOW model

CBOW: We are trying to predict the next word based on the context (defined as a certain window of words around the target word) RNN can also be used for predicting the next word in a sequence, where ...
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Multivariate regression - not enough data?

I have a table with data about 10 agriculture parcels. Each parcel has data in time regard the number of nutrients each parcel has received in each day and in the end I have the total number of ...
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What are more advanced techniques than ARIMA?

For timeseries predication cases, what other techniques are available in statistics or machine/deep learning other than MA (moving average), ARMA, and ARIMA?
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How to use time series datasets that have the same time stamps and features across multiple locations for predicting energy output?

I have some datasets: One dataset is comprised of the overall solar energy/wind energy production of a country. The rest of the datasets contain weather data (temperature, pressure, wind speed, etc.) ...
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How to consider the change in categorical variable in multiple linear regression?

I am building a multiple linear regression model to predict the mileage of tires and one of the independent variables is the wheel position. It is categorical and I could encode it to run the model ...
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1answer
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What is predictive Horizon?

I understand the basics of what predictive Horizon means. When we predict in future, we set up a time window. In other words, it is used to determine how far ahead the model predicts the future. ...
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Using a randomForestSRC model to predict new values always produces the same value

I fit a multivariate random forest model using randomForestSRC, but when I try to use it to make predictions, it always prints out the same value. In the code below,...
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Prediction method when the time series is not sequential?

I have multivariate time series data consisting of monthly sales of contraceptives at various delivery sites in a certain country, between January 2016 and June 2019. The data looks as follows: The ...
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1answer
53 views

What metric should I use to achieve perfect score when choosing all possible results?

A guy told me that he can predict which player I would choose from Greece's Euro 2004 Champion football team. Assume my choice was random. He then goes ahead and names all the players of the team. He ...
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Prediction of rain using DBSCAN and Spectral Clustering [closed]

I wanted to do a prediction model of rainfall after clustering of data. I don't know how to proceed.Is it possible? May be using csv data.
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42 views

How to handle "year" variable for classification

I am writing to you because I need to create a model that tells me whether or not a company will pay its taxes the next month. For that I have data from 2017 to 2020, with characteristics such as size ...
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Evaluation of reliability of suppliers by on time delivery

I am trying to create a weight that can help me properly evaluate the reliability of a company’s on time delivery ratios. I’m using historic delivery data. For example, comparing company A that ...
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Can the same data set (dynamic) be described as Chaotic & Pareto?

I'm trying to abstract the mathematical part of the problem as much as possible before the details follow, There's this dynamic data set that's $O(2^{32})$, a recent result described it as a power-law ...
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1answer
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Rule based prediction for known data

Lets say we have trained our model on 900 records (training data) . During prediction on test data of 100 records, assume model produces 95% accuracy. The question here is, can a mechanism be built, ...
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1answer
295 views

Random Forest. In a prediction less input is expected than features used

ValueError: Number of features of the model must match the input. Model n_features is 2 and input n_features is 7. I have the following error: I have not used any type of encoding(like one-hot etc.) I ...
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Error while using pre-trained model

I'm working on NLP task using RoBERTa model. As training last very long I saved my model, but now for some reason, part of my code doesn't work with this pre-trained model (getting an error), and ...
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31 views

Is there a dataset that can predict duration to complete a task using task description? [closed]

I am working on a problem where the task is to predict how long will it take to complete a given task using just the description as a feature set. The description is something like "pick up X and ...
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1answer
43 views

How do you effectively predict the top 20% most likely customers to churn from a dataset?

I am looking to work out that if I have a dataset with 100,000 existing customers who didn't churn and 20,000 previous customers that churned in the past and the business objective is to target the 20%...
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Time series forecasting for vibration prediction on Industrial machine production?

I'm working on a machine learning project related to an industrial machine. The goal of the project is to build a model that would be able to predict the vibration of the machine while it's in ...
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Minimising inputs for decision tree predictions

It is common for decision trees with asymmetrical shapes to have leave nodes that come early. For example, the model can already generate a prediction if the answer to the first question is FALSE, ...
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Forecasting mon missing time timeseries data

I have time series data for minutes interval. But due to some noise i have to remove some rows from data. Now, I have data with some missing time stamp. What should i do for forecasting in this case?
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1answer
70 views

Keras: Provide One-Hot-Encoded input values to neural network

I have a dataframe which has two columns of interest: A and B with string values. I am trying to build a prediction model which takes in a set of values in A as input and predicts the corresponding B ...
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Multiple Input (Binary) and Single Ouput: How to calculate correlations?

I have a dataset with multiple criteria which are either "passed" (green) or "not passed" (red) and an output (passed or not passed) -> see table. Also the criteria have a ...
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Divergence of Specificity and Sensitivity

I am working on a ML classification project in healthcare. The data is imbalanced, and I decided to start modeling with tree-based algorithms such as (Balanced)RandomForest and XGBoost. While checking ...

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