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Questions tagged [predictive-modeling]

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Statistical techniques used for predicting outcomes.

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Train/Test dataset and model [closed]

I would like to ask you how to work on train and test dataset. I have unlabelled data. They are short text (max 100 characters) and I would need to understand their sentiment. To do this, I am ...
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1answer
52 views

Modeling price vs demand

I have a dataset consisting of products, clients, price policy, discounts, quantities, and net sales. The task as put in words by the business is quantity vs price. I have noted a few observations ...
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19 views

Inverse predict the features from known target with fitted sklearn regressor

I understand that the default way a scikit-learn regressor works is that we fit it to a dataset of features and targets (X_train, ...
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13 views

Using Vector Auto Regression for multiple time series at once

Say I have a dataframe like so: ...
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1answer
20 views

How to predict probabilities from a new data set from an already built and validated model in Python?

I have built a classification model using the following steps (and in the mentioned order) in Python - Data cleaning - Removing unwanted variables and separating Predictor variables from response ...
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2answers
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Checking linearity for a linear regression model?

I've read that there are various assumptions associated with a multiple linear regression model which you should check/validate before getting too excited about your model results. One of these is the ...
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How to develop a likelihood based prediction model to predict chance of rain in a particular hour of a year

I have time-series weather data (from 2005-2018) of temperature and rainfall (every one-hour interval) from three different location weather stations. I want to predict/see what likely be a chance of ...
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2answers
93 views

Stacking and Ensembling methods in Data Science

I understand that using stacking and ensembling has become popular, and these methods can give better results than using a single algorithm. My question is: What are the reasons, statistical or ...
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2answers
32 views

Text Classification : Classifying N classes vs rest of the classes

Apologies if this is naive, I am fairly new to the domain. I have a requirement where I am trying to classify 2 types of text data, i.e, I have got 2 classes to classify my data upon. I am able to get ...
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1answer
15 views

Best Approach to Forecasting Numerical Value Based on time series and categorical data?

Consider a dataset of thousands of car repairs that have been performed. In simplest of terms, the columns to consider are the time of year when it was broken (seasonal changes in demand for car ...
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1answer
10 views

May the training sets of two predictive modeling cases (with an overlap in features) be combined?

Say we have dataset D1 (columns A, B, C) and D2 (columns A, B, D) with target variable E. As both datasets are rather small, their respective predictive models do not perform really well. To improve ...
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1answer
9 views

Propensity model with Only Positive Data

Is it possible to build a propensity model (i.e., the likelihood that a user will buy an item) using only positive values. For example, I have a bunch of data about Customers (people that bought stuff)...
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2answers
43 views

Predict time to reaction (chemical engineering)?

I need a hint on the problem below. This is related to predictive analysis and chemical engineering. I don't background in chemical engineering, and that's why I am looking for some hints. I want to ...
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12 views

Predict all possible dates in time series data

In my problem statement one part is to predict all possible dates(t-n) where t is my current date. I want to process below dataset to predict all possible order dates for next login date(single ...
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1answer
18 views

Ingredients, Recipes and recipe ratings. I would like to predict the rating based on combination of ingredients

I would really appreciate some help on the first steps to my problem, suggestions of modeling techniques i could use or relevant research (i could not find any). I have a list of ingredients (150 in ...
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0answers
15 views

Best methods for Predictive Analysis in Machine Learning?

I'm trying to analyze some data(I get data daily) in R and predict as accurately as I can what will happen in the future. I'm hoping I can predict a few months ahead, but anything that works well will ...
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1answer
40 views

Prediction Outputs from LSTM NN

I'm working with an LSTM network to predict the surface roughness due to biogrowth on ships. I've got a Network that fits the input data I have relatively well, the problem is when I'm using it to ...
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0answers
12 views

Chossing between Prediction vs classification model for dataset having daily record(date value)

I have a use case, where I have 4 classes based on the score, for example class 1 : when the score < 10 class 2 : when the score between 11 to 20 class 3 : when the score between 21 to 30 class 4 ...
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1answer
19 views

Output model from GLM in R

I had generate in Ra logistic model using glm using binomial as family, but each session that I started in R the variable that I used to store the glm output gives me another output. Why this happen? ...
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1answer
16 views

Logistic Regression Multi-level Independent variables

im trying to study logistic regression, when i did the target variable with all features, i had the summary showing the p-values as usual, but one for the features has 60 level, another feature has 13 ...
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Space partitioning to estimate product weight

Looking for some vocabulary to help me refine my research so I can tackle this problem. Here's an overview of the problem statement I'm working on. At my company we manufacture various products, ...
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1answer
27 views

what are the next step after ML prediction and how to proceed?

I have trained an ML model with a good accuracy but what next? I am facing difficulty in answering this question, how will you present your model. Which framework do you use How do you make sure ...
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1answer
22 views

How to adjust/smooth a certain number using constants or rules

Hi, I am handling a dataset with a customer purchase history. The field ord_cnt represents the purchase without coupon usage, and cpn_ord_cnt represents the purchase with coupon usage. There are two ...
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1answer
25 views

best NN architecture for point prediction

I'm training to predict a single value y (continuos in [0,1]) based on a number of variables ...
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1answer
30 views

Prediction for not completely well classified data

I have a DataFrame of users, some of them are "bots" and they are identified with a bit equal to 1 in the "is_bot" column, if the bit is 0, the user is considered as "human". The problem is that some ...
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2answers
25 views

Custom loss function

Is it possible to apply a custom loss function in a regression model (or any other algorithm for predicting continuous variable) ? I'm working on a stock market prediction model and I need to maximize ...
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0answers
12 views

How to calculate final AUC for sequential combinations of binary classification models in Python

I am working on developing a binary classification model using GradientBoostingClassifier on a highly imbalanced dataset (100:1) that I plan to implement in 2 steps. build a model (M1) that will try ...
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Choosing a non-linear regression model and predicting

I'm new to data science and machine learning. I was working on a project and I happened to get this graph. I want to build a predictive model using this, for each of the boroughs. I do understand ...
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9 views

What should I use to model a non-monotonic relationship with values between 0 and 1?

I am trying to find a good model to fit to these curves: They are relationship between the probability of a dispute escalating into war, and the number of disputes in the past ten years between those ...
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9 views

can i compare output from predict_proba with my y_test value?

all, i am a bit confused at comparing my results from predict_proba (which returns an array) to it's dataframe e.g ...
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14 views

Public benchmark datasets posted with expected/record scores for sanity check?

When I use a new modelling tool or approach, I like to do a quick sanity check on a public dataset to make sure I'm getting good (but not "so good it looks fishy") scores. There are several clean, ...
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13 views

Building the right prediction process with machine learning

I am working on a two-class classification model to predict if some lead becomes a sale. At this moment I have all leads try to predict these ones, which are sales. I become good metrics right now ...
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9 views

Predict users $ value based on selections

I want to predict the chance of a user becoming a customer, and subsequently predict their customer value based on inputs from a new user onboarding questionnaire. In the onboarding a new user can ...
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1answer
24 views

How to make prediction using tensorflow models?

As a newbie to tensorflow, I am using this tutorial from google for binary classification using a simple dense neural network. The slightly annoying thing about this (and a few other) tutorials is ...
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17 views

Defining the Target Value

im new to this community and it always helped me with my concerns, i looked for an answer but didnt find a clear one yet im working on study for insurance default, the data i received is already ...
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0answers
11 views

When should I reverse normalizations to evaluate loss?

If I am training a neural network and have normalized the data before-hand, should I reverse the normalization to calculate the loss? This tutorial provides an example of this method. What if I'm ...
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3answers
35 views

Does shuffling data for time series forecasting help?

So I am trying time series forecasting using LSTM's. The aim is to predict $Y$ given $X$ using regression. I had already converted the input data into a sliding window format such that if my input ...
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1answer
51 views

Logistic regression based prediction model using flask(python) to predict if Student will pass or fail. Error [duplicate]

I am trying to create a web application on Python using Flask that predicts if a student is likely to pass or fail using a Kaggle dataset. I changed the dataset a little and want to predict if the ...
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1answer
13 views

Low leves of probability observed after modelling.Is it right to scale the probability

I have done modelling on imbalanced class , without any sampling methods. Event rate is around 0.1 ,After modelling I am getting probalities more at the lower side close to zero.I have tried differnt ...
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1answer
39 views

What's the best way to predict weekly selling data?

I am trying to create a model to predict the units that will be sold for different grocery items say in the next week. I am structuring the problem in a three-step procedure. Group together the ...
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1answer
41 views

Two-class model with predicted scores needed - classification or regression approach

In my problem, step one is to build a model to classify cases as one of True or False (1 or 0 could also be used obviously). Once the optimum model is found, step two is to retrieve probabilities for ...
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1answer
20 views

Predicting a timeseries that includes categorical and numeric data

Given the following properties in a dataset: Type Of Work [T1,T2,T3,...Ti] Measurment Unit [U1,U2,U3,...Ui] Number ...
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Predicting next failure of car system given previous failures

I have a Dataset of cars including various features just as energy used, power, the model year, rolling law (maximum number of kilometers the car should drive per year) etc. I have also some ...
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0answers
20 views

Which type of model should I use to predict when a time-series value will revert towards the mean?

I have a time series that consists of many rows, each with a timestamp, and a value between -1 and 1 representing the normalized price distance between 2 financial assets. Each entry is roughly evenly ...
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1answer
59 views

Hill Climbing Algorithm - Optimum Step Size

I am implementing a standard hill climbing algorithm to optimise hyper-parameters for a predictive model. The hill climbing algorithm is being applied as part of a two-stage approach: Apply grid ...
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1answer
11 views

how to perform minmax normalization on large dataset?

I have problems loading it at once. I guess this problem applies to compute all the variables that need to take the whole dataset.
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14 views

Weighting Value Of Timer Series Event Based On Subsequent Events

I am new to Data Science forum. I post a lot on StackOverflow, but this issue is more conceptual. I am doing analysis on time series data and weighting the value of an event based on the outcome. ...

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