Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
669
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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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0answers
21 views
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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1answer
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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1answer
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 ...
3
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1answer
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 ...
2
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1answer
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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1answer
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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1answer
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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3answers
49 views
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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2answers
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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2answers
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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9 views
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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1answer
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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1answer
8 views
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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1answer
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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1answer
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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14 views
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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2answers
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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7 views
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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2answers
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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0answers
17 views
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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0answers
8 views
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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1answer
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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0answers
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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0answers
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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1answer
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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1answer
17 views
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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0answers
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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1answer
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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2answers
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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15 views
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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1answer
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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0answers
16 views
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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0answers
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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1answer
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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1answer
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 ...
3
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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 ...
2
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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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2answers
24 views
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 ...
