Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
699
questions
2
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1answer
51 views
Predict the corresponding value in one column using a list of values found in another column
Please have a look at this link. This was a question I asked few months back and after some suggestions and exploring I was able to successfully use TFIDF along with MultinomialNB classifier to pretty ...
1
vote
2answers
93 views
How to visualize Ensemble Models ( Random Forest) with 1000 estimators
I am working on classification problem where I need to categorize the user in buy/ non-buy category. I have around 100 + features or predictors to predict the behavior of user.
I tried to implement ...
0
votes
1answer
68 views
how to build a predictive model without training data neither historical data
I m trying to score "how much a product is expected in the market". I created some features:
How much this product is used each year.
Where was it used .
how many product for each country.
the main ...
0
votes
1answer
99 views
Exploratory Data Analysis
I am working on this dataset.
Dataset has missing values. What would be the best method to impute the missing values. Also values are missing from target feature as well. So far I have dropped those ...
1
vote
0answers
95 views
Improving population weighting
Bit of a noob in this stats world, so apologies in advance for any naiveté. I did a fair bit of stats long ago in college but it's a distant memory, so please assume little knowledge!
The dataset I'...
2
votes
1answer
128 views
Probabilistic Outlier Detection (edited + clarified)
Measured data $D \in \mathbb{R}^3$, every $d^i \in D$ is $d^i_{(x)}$, where the $x=[x_1, x_2]$. Simply said, the measured data are function of $x$. It is known, the dependency is linear, such as:
$$...
2
votes
1answer
5k views
Keras Conv1D for simple data target prediction
I am trying to use conv1D layer from Keras for predicting Species in iris dataset (which has 4 numeric features and one categorical target). Following is my code:
...
2
votes
2answers
47 views
What methods can be used to detect duplicacy in image dataset?
I want to remove duplicate images from a dataset of 50Million images. What is the best method to detect all the duplicates?
Do you think one shot learning is good for this?
0
votes
1answer
162 views
Running multiple random forest and combining them
I am trying to build a random forest model in R (RStudio). My training dataset has around 2 million rows and 38 variables. When I tested 5000 rows from this dataset I was able to build the random ...
1
vote
1answer
22 views
Algorithm Suggestions for a Self Project [closed]
So, I am doing a small self project on data analytics. I am collecting the android apps data from the play store sites by web scraping.
I am basically trying to collect all possible information ...
1
vote
1answer
46 views
Fully endogenous models for predicting multivariate time series
I have a formal social science background but I am new to data science. My interest is in building predictive models for applications in the social sciences, mostly (but not only) in economics.
I am ...
1
vote
0answers
14 views
How can cognitive neuroscience enhance machine learning?
There have been many recent papers on using cognitive neuroscience as inspiration for the improvement of machine learning.
For example, Hassabis et al. (2017) have written an article on ...
2
votes
1answer
90 views
How to create user and item profile in an item to item collaborative filtering? (Non-rating case)
I want to build a recommender system for a coupons website which should do the following: Given the past purchase behaviour of a user, recommend coupons which the user is likely to buy. The data does ...
1
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0answers
20 views
Decision tree to get difference in rates in two groups?
I have two sample groups of customers, each customer has 100s of features. For a single sample, i would use Decision Trees to find sub-groups that have a high churn rate. Thats easy.
However, my ...
0
votes
1answer
30 views
Higher frequency of time series benefits
We are setting up an experiment for a model that is able to predict the evolution of a time series in different horizons. One of the parameters to decide is the granularity of frequency of our samples ...
2
votes
2answers
100 views
Which recommender system: Content based or Collaborative filtering?
I want to build a recommender system for a coupons website which should do the following:
Given the past purchase behaviour of a user, recommend coupons which the user is likely to buy.
The data does ...
1
vote
0answers
15 views
Classification on time series items - choose not constant threshold
I'm dealing with a classification problem on a time series {time: t, value: y(t)} where, for each time t,
my classification algorithm gives as ouput the probability that the y(t) belongs to class 0 or ...
1
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0answers
29 views
one predictive methods
Is there any algorithm/method/system/application that combine all predictive methods into one?
so for users instead of deciding which method they should use, is there any platform that you just feed ...
1
vote
1answer
40 views
Which model may be best for outcome of a surgery?
New to data science and am trying to be a self-starter and implement advanced data analytics in my subspecialty of surgery. Below is a description of my data set. I know that I will have to explore ...
3
votes
1answer
31 views
Predicting t+1 from a set of sequences
Say I have have an experiment where I release a single rat into a maze and wait for it to reach the end. Say I also track this rat's position in the maze at various times. Let's do this $n$ times. Now,...
1
vote
1answer
134 views
Timestamps in Ridge Regression Scikit Learn
I am trying to transform data for use in regression, most likely the Ridge or Lasso technique implemented in sklearn.linear_model.
My training data contains time ...
1
vote
0answers
39 views
multi-targets predict using python
let's say I have year month data h1 h2 h3 .. h24
2004 1 1 40 42 60 ..
: : :
2008 12 31
I am trying to predict h1....h24 for a ...
1
vote
0answers
18 views
Having the target and data row - how to find the correct model
I am coming from a web developer background, and having no data science background.
I am looking to skill-up and get some answers for a current task: find a model that returns a predicted value same ...
5
votes
1answer
87 views
Why does a machine learning algorithm need a bias?
The first line of section 2.7.3 in Mitchell's Machine Learning is:
"A Learner that makes no prior assumptions regarding the identity of the target concept has no rational basis for classifying any ...
1
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0answers
16 views
Link Prediction based Similarity Indices
So, I was reading some Link Prediction based algorithms and similarity indices. I came across two random walk based indices - Local Random Walk(LRW) and Superposed Random Walk(SRW). I read the ...
1
vote
1answer
59 views
What model can I build with a limited dataset?
I have a dataset consisting of purchasing history from an e-commerce website. The columns consist of customer id, product id, <...
-1
votes
2answers
981 views
forecasting revenue
Does anyone have any recommendations on how I would go about forecasting Microsofts revenue using python + time series or ML (recommended techniques e.g Random-forest). (I have past revenue and share ...
0
votes
1answer
94 views
Predicting binary target value based on unlabelled features
I have a dataset of around 15 stocks having the following data format :
...
0
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1answer
39 views
Confidence of this particual prediction
I am looking for a confidence of model to predict well in a given situation.
So I have a model $f$ (generic, let's exemplify with a regression model of explicit form for brevity).
It well fits on the ...
2
votes
0answers
88 views
decision tree vs neural network for boolean function
Which structure is more powerful in terms of expressiveness (i.e. it can represent a given Boolean function, accurately) — a single-layer perceptron or a 2-layer decision tree? (There are 10 features)
1
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1answer
2k views
How to combine two Deep learning model weights into one
Suppose I have these two models (model1 and model2) trained from same structured data, but different datasets:
...
1
vote
1answer
45 views
Predicting Composition of Chemical Compounds
I have a dataset which has names of compounds and their compositions. Like below
Sulphuric Acid=>[H,S,O] (Hydrogen, sulphur, oxygen)
Oxalic Acid=>[H,C,O]
Sodium Oxalate=>[Na,C,O]
Potassium Sulphate=>[...
3
votes
4answers
376 views
When should ordinal data be represented catigorically and when as integer?
I am doing the Kaggle competition House Prices: Advanced Regression Techniques to learn more about data analysis. I would like to apply multiple models to the data(Regularized LR, Random Forests, ...
1
vote
2answers
247 views
Train an LSTM neural network with time series containing seasonal and trend
I am working on a project for predicting the number of DNS queries from the site:
DNS queries statistics. The data I use is minutely data, which means the number of DNS queries of every minute.
If ...
1
vote
1answer
46 views
Logistic Regression or regression SVM for probability of outcome
I am working on a prediction question: what's the percentage of Y = 1 using a number of features?
The output Y values I have for training are in binary. In this case, should the prediction be ...
1
vote
1answer
26 views
Building a model to predict how likely someone is to answer the phone based on past call history and demographics?
Imagine you have a list of everyone in your network. You want to know how likely they are to answer the phone. There are several people in your network that you have called multiple times (some of ...
0
votes
1answer
49 views
Can we make two separate models vs one for classification?
Suppose I have a binary classification problem and my data is imbalanced, I can build a classification model using any of the algorithms and use an oversampling or undersampling technique to handle ...
1
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0answers
17 views
How to get maintenance interval from maintenance outcomes?
I have a machine, which needs maintenance.
Every time the technician visits the machine, there are four possible outcomes:
a) The machine is broken, b) The machine is still running, but it's high ...
2
votes
2answers
32 views
Is there any logic to adding a threshold to see if two variables are related?
I have two variables $X$ and $Y$ given as tuples of $(x, y)$, and I want to see if there is a relationship between the two variables. I can do so by finding the correlation coefficient.
However, I ...
1
vote
1answer
743 views
LSTM Model for predicting the minutely seasonal data of the day
I am making a model for predicting the network traffic volume for our data center.
Let me describe my dataset first. At this time, we have the model of 90 days, on each day, we record the network ...
0
votes
3answers
30 views
classification performance metric for high risk medical decisions
What is the best classification performance metric for risky medical treatments like surgery? for example a patient should NOT suggest a surgery (negative) if he/she can be treated by medicine (...
1
vote
1answer
93 views
Dealing with a dataset having target values on different scales?
I am currently working on a dataset having 10 features and one continuous target variable. One of the features is 'Country' , in which there are seven unique values [Argentina ,Denmark , France...etc]....
0
votes
2answers
73 views
Why does prediction by a consensus of classifier work better than prediction by a single classifiers?
I have seen that consensus of classifiers (taking say 5 separate classifiers) and obtaining the final labeling of the unknown sample based on the voting method (whichever class gets the predicted the ...
0
votes
1answer
152 views
Skills based recommendation system
Assuming that I have a list of Users with a list of skills: (each value is a different skill)
And a list of Tasks with a list of demanded skills:
Based on a manual classification that returned: (...
1
vote
1answer
76 views
Machine Learning for user modelling
I have a dataset where each row is a interaction of a user with a content.
I have user's features to represent the user (each user is uniquely represented through user.id):
...
1
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0answers
24 views
How to decide which forecasting model to use? [closed]
So I have a sales forecasting problem where I have 3 years worth of data about weekly sales of a certain company.
There are 3 types of retail stores in that company, Type A, B, and C. There are a ...
0
votes
1answer
246 views
Titanic Kaggle Data: Why am I getting lower accuracy on Kaggle submissions than on held-out data?
I am going through my first solo machine learning project and would like to gain some insight into what I am doing wrong/what is going on here as I am a bit stuck.
I have been applying machine ...
0
votes
1answer
104 views
Inference of root mean square value in terms of house prediction
The objective of the task is to predict the housing prices. A model is created based on California housing dataset to predict housing prices and is subjected to evaluation using the below code.
...
1
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0answers
37 views
Taking advatage of the frequency of an outlier
I'm doing outlier detection (Conditional Outliers) on a multivariate time series. The outliers appear every 2 weeks $\pm$ 4 days.
How can I incorporate this prior in my models, to reduce the number ...
1
vote
1answer
61 views
Need help on Time Series ARIMA Model
I'm working on forecasting daily volumes and have used time series model
to check for data stationarity. However, I'm strugging at forecasting data with 90% accuracy. Right now variation is extremely ...
