Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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16 views

Predict time to send mail

I have a dataset which contains data on when an email was sent and when an email was opened, so I would like to build a model to predict when an email will be opened. I will then use this information ...
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How match output (pred value) to input value

I'm working with data(with 4 columns which are p(product), M(name of the store)), I want predict the demand of store for that I sued SVR on the data by theses formulation: ...
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Which methods can I use to optimize my regression model so that it avoids predicting below the real value? [closed]

If I'm trying to predict something like "units sold" of a certain product to estimate the stock that I'll need. Which statistical methods or metrics can I use to train my model to avoid ...
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Should I give regularly-spaced or irregular-timestamped data to a price predicting neural network?

I am building an application to predict the price of an item. Data is collected at regular 5-minute intervals while the application is running. Unfortunately, there is downtime, so there is not a full ...
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Dealing with unseen data/categories in machine learning models for stream data

I want to build a machine learning model (xgb and lgbm) that has to handle streaming data on a weekly basis. The models are trained on a bi-weekly basis. The data includes order information and I want ...
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Is there a way to duplicate time series data?

Context: I want to work with a corpus of ~800,000 scientific abstracts from 1970-2017 and predict trends in another corpus. Problem: There may be insufficient data to accurately predict trends between ...
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Does the model(best fitting line/curve) changes when the training data is changed in the cross validation?

From my understanding - a machine learning algorithm goes through the inputs (independent variables) and predicts the output (dependent variable). I believe, what line/curve would best define the ...
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How to determine activation functions for neural network

I am trying to plan a neural network for regression predictions. The final activation layer should be a linear function, but for hidden layers, do the activation functions need to also be all linear ...
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How to find the relationship between one dataset and two others?

From a STEM problem, I vary a variable x within a range and calculate quantities $U(x)$, $V(x)$ and $W(x)$. I want to figure out an analytical relationship between unknown $U(x)$ and the other two ...
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Is there enough datapoints to make a reasonable predcitction?

I am planning to use this dataset (for a school project) in order to determine the most important features in predicting whether a student will receive a placement. Further I would like to create a ...
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How to best determine trim values for a trimmed mean calculation

I am designing a model for a processing facility. This facility runs certain processing steps on products. Depending on certain details of the product/step, these steps are grouped together into step ...
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How to prepare/optimise data for FP-Growth algorithm

I'm using spark mllib for FP-Growth algorithm for our ML model. Description of my issue: I have taken transactional data from our production database to mine the frequent brought items recommendation. ...
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Modeling a time series quantity by modeling its constituent time series

I have a time series target, let's say $Y_1$. This quantity depends on two other time-series quantities deterministically, $Y_2 \text{ and } Y_3$. That is, we have some function which takes $Y_2$ and $...
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How to find False discovery rate of a ML model? Situation explained below

Lets say:- ML Model denied 1000 transactions FDR= FP/(FP+TP) I randomly picked 400 accounts and checked if the model denied good user or bad user. Good user denied- 110 Bad user denied - 290 How will ...
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Which PreProcessing method should be used?

I have a dataset that consists of a poisson distribution, a exponential distribution, categorical variables, and my target variable is a numerical bimodal variable. This is a regression model. I ...
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flexibility vs complexity vs number of predictors in machine learning

I'm new to machine learning so am quite confused with the above concepts. It seems to me both flexibility and complexity measures how well the model fit the data (in terms of the curvy-ness), so what'...
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Any tips on transfer learning for a regression problem using 4D images as input?

I developed a CNN based on EfficientNet in order to predict the weight of piles of some materials in an image (the labels are the weights in kg and the input is RGBD tensors of the object). I have two ...
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Impute missing values in feature column on the basis of Target column

I am working on a toy project for insurance claim prediction. In the input data for one of the feature (numeric data type) half of the values are missing. My target variable is binary which indicates ...
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Terminology of time series

The terms Time Series Analysis, Time Series Forecasting, and Time Series Modeling are widely ...
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Is it possible to change the input columns of a trained ML model while making predictions from it without affecting the accuracy?

Consider the following scenario. I have trained a K-Means model on some input features, say, (A, B, C, D and E). Now at the time of making predictions I want to make the model predict using only fewer ...
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Update machine learning model while retaining the prediction results exact for old data

New to ML here. In our industry, we are looking for a type ML method/model that can be updated to accommodate new data points while keeping the prediction value of the historical data exactly the same....
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Which data sets would help to predict (exponential) market trends?

Which kind of datasets do websites such as MeetGlimpse, trends.co, explodingtopics.com use to detect exponential market trends? I love them (not affiliated) and would like to better understand how ...
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Forecasting monthly visitor count from daily values

I have a dataset of the daily visitor count of a website. Given this information, I want to forecast what the monthly visitor count will be. Depending on the visitor count on a day of the month, I ...
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Whether Interaction terms should be included in Linear Regression analysis?

I am working on a linear model with 6 independent variables and when thinking about including an interaction I got lost. An interaction exists if the level of one independent variable is affected by ...
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Machine learning and time-based data

I want to predict conversion rates for an eCommerce store. I have data from Google Analytics with features like averageSessionDuration, bounceRate, numberOfVisitorsBySource etc. and the corresponding ...
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Unstable Training when combining Graph Neural Networks for Graph Classification Tasks

I have been combining Graph Convolutional Layers and Graph Pooling layers to define a neural network architecture for Graph Classification tasks. Specifically, using the Graph Convolutional Layer ...
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How many images can be trained in Google Colab? [closed]

I am using the ResNet50 pretrained model to train my images using TensorFlow. I have 70k images and upgraded to Google Colab Pro, but still I am facing a memory error. So how many images I can train ...
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Interpreting the results of the probabilistic neural networks (Monte Carlo dropout approach)

I have a Keras NN model where I apply the Monte Carlo dropout approach as a predictive method to evaluate the uncertainty of the model outputs. From my research in the probabilistic neural networks, I ...
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Calculating Uncertainty for categorical predictions

I am wondering what is the best way to calculate the uncertainty for my categorical predictions. I have created a model that predicts what rating a movie is getting based on certain keywords and the ...
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How data are prepared during training, testing and in production?

Most of real world datasets have features with missing values. Replacing missing values with an appropriate value such as its mean, is considered as a good step in feature engineering. Some times we ...
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Classification model performance - metrics for getting number in each class correct?

I'm fairly new to predictive modelling, so apologies if this is a stupid question. I am working on a classification problem (predicting if customers commit fraud or not), and have been comparing a few ...
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Metric to punish positive errors

I'm involved in a ship transit time prediction project. Is about prediction the time that a ship's cargo takes to go from port A to B in order to contract the fastest carrier company and tell the ...
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Predict the target audience for a new brand using data from other brands and customers buying behavior

Assume a company has a large database about wine, including brand, the taste of the wine, year, place of production, etc, and data of customers' purchase behavior. Now if there is a new brand coming ...
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After training and saving a model can we give more information as input?

Suppose my data is a time series with multiple features such as wind, temperature, holidays, etc.. and I'm predicting a target variable Y. After I go through the whole process of splitting data into ...
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How to ouput buckets of probabilities?

I am dealing with an unbalanced binary classification problem. The problem is so unbalanced (2:98) and hard to predict that I am interested in probability of the positive outcome instead of trying to ...
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How to predict auction winning price without knowing the winning price when you lose the auction?

Suppose I participate in online auctions. I submit bids based on the features of the item being sold, but I only got feedback when I win. If I lose, I would know nothing about who won, and how much ...
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1answer
23 views

Using Information from the rest of a Sequence to Predict the Label for any one Item

I have a dictionary of variable-length sequences: [(file_name[-10:], len(tag_is_header_list)) for file_name, tag_is_header_list in HEADER_PATTERN_DICT.items()] <...
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Predicting the likelihood that a prediction from a linear regression model is accurate

So to set up the problem: I have a data set that had labeled data like colour, brand and quality as independent variables and the dependent is RRP (price). I have made a linear regression model using ...
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1answer
53 views

Model retraining

I have trained my model with RandomForestRegressor, but now my training data is updated continuously. So I have to train my model with all the train data set i.e past and new data, or can I directly ...
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44 views

How to predict variables based on multiple samples?

The problem I tried to do some ML models but everytime I had some weird plots and I couldn't understand these scores. I'm relatively new to ML and maybe someone can help me with this data with some ...
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Is it possible to create a predictive model for a dataset that consists of only positive occurrences of the dependent variable?

Lets say I want to predict earthquakes. My dataset would only contain data about earthquake occurrences and no data about non-earthquake occurrences as that would basically be any other period of time ...
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How effective would a data-driven vaccination program be over a simple rules based approach

The rollout of vaccination programs tends to be based on a given set of rules (advice) devised by government UK example. Such a rule-set are generally limited in complexity in order to be consistently ...
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How to handle One Hot Encoded columns with changing categories in supervised ML Problem?

Scenario: I have the following game data about participants, game and the winner in the following format: ...
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multi items forecasting: issue with storing results

disclaimer: I am not 100% sure that this is the appropriate place to ask this question. Here is a little bit of context about the problem. I have a dataset containing about 1000 products timeseries (...
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1answer
25 views

Relationships between groups of features against independent variables

I have several groups of features that I'd like to test against independent variables. The idea is to find which groups tend to be associated with a specific value of an independent variable. Let's ...
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How to Include Features that Apply to Specific Classes

I'm predicting hours that will be worked for building tasks. Due to the overall low sample size, I've stacked multiple related tasks together into a single model. (There may be 100 total samples in a ...
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Prediction using OSM and Airbnb Listing dataset

I am building a model to predict the price of an Airbnb listing. Using OSM("https://wiki.openstreetmap.org/wiki/Downloading_data") and Airbnb listing("http://insideairbnb.com/get-the-...
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Predicting an annual event – modeling on an annual or monthly basis?

Suppose I'm interested in predicting which of my current customers are likely to renew their insurance at some point in the year. The renewal can happen at any time in the year. I want to proactively ...
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how to interpret this 'lift chart'? prediction and true labels

i am trying to compare the prediction from my classifcation model and it's true label either 0 or 1. ...
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1answer
71 views

Negative R2_score Bad predictions for my Sales prediction problem using LightGBM

My project involves trying to predict the sales quantity for a specific item across a whole year. I've used the LightGBM package for making the predictions. The params I've set for it are as follows: <...

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