Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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15 views

Any idea on how to model this specific data distribution. See attachment

I am trying to fit a curve on the data( in the attached image). I see that there is a lot of variance in the response variable for each explanatory variable value. I am not sure how to model this. I ...
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Why do you need to use group lasso with categorical variables?

From what I've read you should you use group lasso to either discard the dummy encoded variables (of the category) or use all of them. If you use normal lasso then some of the variables in the group ...
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22 views

How to test model accuracy on new vs. historical data?

I created an XG Boost model to predict churn using a dataset of customers who were sold during 2018. The accuracy of the model is 89%. Does it make more sense to re-pull the 2018 dataset, where more ...
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14 views

Train and predict on a varying number of inputs - time based events

I have the problem where I am trying to build a model which takes in n events for a single user as input for prediction, the problem is that the number of events is ...
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17 views

How to use fresh data when target prediction period is long?

I'm using supervised learning on monthly activity data to predict when a customer buys a particular product. This product is typically bought infrequently and at the moment my target variable is ...
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25 views

Predict Customer Next Purchase with Sequence

Suppose I buy products: [1,2,3,4] Another customer X bought: [2,3] Most probably customer X next purchase will be: 4 Sequence is very important in my problem I tried association analysis using R, ...
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8 views

H2o Flow Model creation Notification for external application

I have a requirement.I would like to trigger an event from h2o flow (through RESTful API preferably) whenever I create a model in h2o flow webUI - for.e.g ,the moment I create model M1,I would like my ...
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35 views

Which classification algorithms are negatively affected by class imbalances?

I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
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9 views

Strategy for unrecorded predictors

I'm trying to create a logistic regression model for predicting future admissions based on historic clinical/utilization/demographic information. Although I have three years history available, for ...
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1answer
37 views

Include time as a variable in regression model

I am currently working on a regression problem which requires me to predict the costs of a fixed asset. I have used several variables to do so and derived a predicted cost. However, my superior has ...
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16 views

How can I get an algorithm to have an evalutation metric based on aggregate predictions?

Let's say I have a model that makes a prediction per individual. An example data set is below. Normally, evaluation metrics (for example within the XGBoost algorthim), are used at the individual ...
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31 views

My model is overfitting though i'v been using regularization techniques

I've been training an Xception model to recognize the disease of a plant from its leafs. So far i reached a training accuracy of 91% but the test accuracy is around 73%. So obviously my model is ...
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40 views

What algorithm is best suited to derive the best match between two people in a data set?

Say i have a large data set that contains the following data; ...
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19 views

Time Series Forecasting with RNNs

I'm attempting to develop a recurrent model to forecast the value one step into the future (i.e., $x_{t+1}$), given its history $(x_{t-h},\cdots,x_{t})$, where $h$ is a fixed hyperparameter for the ...
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10 views

Compare large prediction with observed values

I have test scores for a lot of schools and I created a performance index calculated using the last score of a state test. This index is supossed to predict the performance of the school in the next ...
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27 views

Are there any rules regarding correlation between the variables used in a CNN?

I was wondering if there are any rules regarding correlation between the predictor variables or between the predictor and outcomes variables of a CNN. What should be the value of correlation? Does it ...
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What's the best way to approach a regression problem with a lot of features (over 300), many of which are categorical?

I have $20,000$ training examples of various candidate attributes (highest level of education, country, year of formal training completion, etc). My output (prediction) will be for ...
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19 views

Keras input for multivariate classification with LSTM using current features and previous timesteps features and y values

I am working on a multivariate binary classification problem. What I want to do is to predict a binary classification given the features at the current timestep and the data (features+real ...
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60 views

Is it valid to shuffle time-series data for a prediction task?

I have a time-series dataset that records some participants' daily features from wearable sensors and their daily mood status. The goal is to use one day's daily features and predict the next day's ...
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Predicting tool breakage on a CNC/VMC machine using Machine Learning?

I data of a fixture (which holds a component during machining) as vibration in 3 direction, the pressure of hydraulic, and proximity. I would like to know when the tool might get broken in the near ...
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42 views

Why n-split is not possible for a dataframe with KFold?

On running below code on python 3.7, I am getting the following response: 'DataFrame' object has no attribute 'n_splits'. How to get rid of this? ...
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Product Prediction to group of customers

I have multiple groups of customer, say for segment 1 as shown in the pictures, I have a list of products that I can choose the cross-sell to that group. Consider ...
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23 views

What is the interpretation for quadratic functions?

I am working through the book Applied Predictive Modeling and came across something that was a bit confusing. It discussed adding non linearity to a model to improve its fit - I get this part. For ...
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32 views

How to apply a trained Random Forest model to a new data set in R?

So I have a data set that is essentially football players statistics in 2017 and 2018. I have trained my model to use the 2017 data to predict the 2018 number of touchdowns. My code is below: ...
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Reducing the dimensions of data who's predominant categorical feature, its layer, has depths that overlaps with other samples layer values

I am working with a data set of soil types with multiple layers of varying depths and sizes with multiple features. There are $1-9$ layers each with differing dimensions, for example, a soil type ...
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105 views

Why is r squared lowered when adding polynomial features?

I am trying to find a best fit line f(x) = ? for a random set of x,y coordinates. Linear Regression with polynomial features works well for around 10 different ...
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1answer
30 views

How to predict based on multiple samples?

I am relatively new to ML so I apologies in advance if my question shows lack of understating of the field. The problem A particular study course has a high drop-out rate and we want to reduce it. ...
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What is the use of detectors in Negative Selection Algorithm?

I understand the main idea of Negative Selection Algorithm is basically derived from the artificial immune systems of what determines something to be self and non-self, and that the algorithm revolves ...
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38 views

Is there any time series model which handles data at variable frequencies.?

Goal: Predict the yellow points.(yellow events appear at varying frequencies) But I'm struggling to find a good model to fit this use case. Most of the time series algorithms are handling data which ...
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Build model to get daily probability of meeting a certain end of period goal

I was hoping for some consultation and direction with how to go about the following: To give context, I work for an agency that manages advertisements on social media for general motors - ...
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What is forecast horizon measured in?

I am using Microsoft Azure machine learning platform and when using the forecast feature it gives me the field of forecast horizon that uses an integer. Does the integer mean days, weeks, years, etc. ...
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47 views

Predicting future automobile sales

I am new to Machine Learning. Recently I am trying to build a model to predict the sales of a particular automobile make and model of a dealership and to which location. The data given to me has ...
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40 views

Machine learning model for determining whether a transaction is cheap, fair, or expensive,

I am currently working on a final project related to data science and would like some advice. I have a second hand bike selling data set that consists of around 100,000 observations with the ...
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81 views

Out of stock / Spike in demand prediction

The goal is to predict out-of-stock situations, either quantitatively (the gap) or qualitatively (out-of-stock likely to happen in next few weeks). Background: We have existing demand planning ...
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28 views

Using predicted probabilities and bayesian inference to update beliefs

I'm currently working on a project to predict the likelihood of an outcome. I'd like to implement a system where the belief the event will happen is updated after running the model on new data. ...
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Data Structure For Multilevel Analysis

I am little confused about how to structure my specific data for multilevel analysis. I have 10 categories and each category has some items in them. The dataset is available for 117 weeks. There is ...
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1answer
40 views

Is there a Feature selection process for ARIMA model?

I have a dataset representing sales per day for certain products. It contains 30000 observations and 6 features (target included). Since my task is to make a prediction about the number of pieces sold,...
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22 views

Target Variable Encoding for Time Series Change point detction

I am working on a time series data for which I intend to impliment machine learning model for detecting change point in time series data. This data is recorded fom machinary and we have to predict ...
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21 views

How to distinguish between normal fluctuation and outliers in ARIMA model?

I have a dataset about sales per day of certain products at the ITEM/DAY/STORE level , I've plotted the series and visually examined it for any outliers, volatility, or irregularities. And this is ...
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25 views

In which predictive tasks are the ARIMA model useful?

I'm working on a project where I have to predict the total quantities sold at the ITEM/DAY level. As a model, I thought of using an ARIMA (I'm using R), but I wanted to get a confirmation of whether ...
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Different sensitivity analysis

I have a metabolic model written in python and I would like to do a Bayesian sensitivity analysis on it to see which parameter affects it the most. Is MCMC sensitivity analysis the same as Bayesian? ...
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33 views

Relating two data sets at the row level where table one may correlate to zero or more rows in another

I'm just looking for some high level recommendations on libraries, design patterns, or algorithms here. I obviously don't expect you to build a model for me. I would like to predict the monetary ...
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Choosing predictive model for dataset

have a question about the type of model which I should use for a dataset I have. I have use 2 data-sets for my project. After hypothesis testing, I me Out of the 7 input variables, 6 of them are ...
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22 views

Choosing loss function in Keras for prediction binary_crossentropy or categorical_crossentropy

What loss function in keras should I chose for binary_crossentropy or categorical_crossentropy? I have data like : $w1,w2,w3,w2,w2,w1,w3,w5,w9,w5,w4...$ I want to predict sequence: input: $w1,w2,w3$...
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28 views

Choice of method for classification and/or duration prediction

Let's consider an e-commerce problem. I have data about users that almost place an order online : they give some information about themselves (name, age, etc.), but won't immediately validate the ...
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16 views

About 1M rows of data. Should I restrict myself to few columns as well?

I'm trying to build a predictive model from about 1 million rows of data. My goal is to predict a certain numerical value. I have the intuition that I should use very few numerical binary columns so ...
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1answer
43 views

Next year forecasting with monthly data from many, correlated, non-monotonic trends

I have trend data from many health departments in a local territory (eg. cardiology, orthopedics, etc...). These trends represent health service (visits, diagnostic, admissions) production, service ...
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1answer
33 views

Transfer learning for a regression problem

if my understanding is correct, in case of image classification and NLP, if I have a pre-trained model, to train on new data, I can reshape the data according to the pre-trained model. So there is no ...
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25 views

Predict vs. Impute: Filling missing data using Random Forest

I am using R package randomForest to build a Random Forest model for classification. Ultimately, I need to choose one of five programs for a group of individuals ...
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What should I check if model accuracy is no better than baseline level(random guess)

I have a data with only 8 columns: id created_time employee_id rank position hourly price num_work_completed work_category hired Hired is the target variable with 1 representing hired and 0 ...