Questions tagged [data-science-model]
The data-science-model tag has no usage guidance.
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2answers
21 views
Reg. Pandas factorize()
-Hi Experts-
I just read about factorise() function in Pandas. Using this I'm able to encode (enumerate) my string values into numbers. But, now I'm not able to understand what numbers corresponds ...
0
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0answers
5 views
How to perform T-test and chi square test to my categorical variables like country, education and predict accuracy using logistic regression?
I'm new to Data science. I have been working on a classification project which has columns (Sex, Age, Occupation, Marital Status, education, country, relationship,capital gain, income). Here income('&...
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1answer
19 views
0
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1answer
5 views
Choose a binary classification algorithm [on hold]
I have a dataset like this:
550 rows
15 binary features(0 or 1)
1 binary target variable(0 or 1)
I want to build a classifier with 80% of the above training data. Which algorithms should i try? I am ...
0
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1answer
17 views
Predicting for future date
How do I predict a category of data for a future date ?
Example: what will the Sales figure for region (or region wise) for a particular date in the future based on the sales person past data for a ...
0
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1answer
15 views
checking model stability - Performance for different class
I tried to do multi-class classification problem. The goal is to predict whether the match will be won by HomeTeam, AwayTeam or Draw. I did feature engineering from the attributes and finally came up ...
1
vote
1answer
29 views
What are the limitations while using XGboost algorithm? [closed]
Will XGBoost pose any problem while dealing with categorical variables with more than 2 levels.
For example, occupation variable can have values like doctor, engineer, lawyer, data scientist, farmer e....
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0answers
5 views
Probabilistic search engine user behavior markov models
I am considering the following probabilistic Markov model of actions of a user on the results page of a search engine.
The user examines the first result, with a probability $A$ he is satisfied with ...
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1answer
12 views
0
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0answers
50 views
ValueError: Found input variables with inconsistent numbers of samples: [1, 0] [closed]
Heres the code...
...
1
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1answer
28 views
How to mathematically explain the translational and rotational invariance of PCA
There is a homework question for a course I am self studying (not a student) that is:
let our $n \times d$-dimensional data vectors be denoted by $x_1,\ldots,x_n$ and let $R$ be a $d \times d$ ...
1
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0answers
11 views
SMOTE caused my total nrows in train to fall to a very small proportion
I have a highly skewed dataset with minority class in target being just about 4%. I decided to apply SMOTE using library DMwR in R. Here is my target:
...
0
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0answers
3 views
Game Data Analysis (Stats)
Analyzing some game data and wanted some help to know how a specific column affects the game economy dynamics.
Game Scenario:
• This game data comes from a video game in which players earn items ...
1
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0answers
14 views
Keras - How to using Cnn trained model on video image.?
I have trained Cat and dog image using CNN with Python ( total 10K, 8K for training and 2K for testing ).
I want to make prediction in a video. Video Contain both cat and dog at a single moment. How ...
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0answers
14 views
How to classifying/Identify both cat and dog image in a single image?
I have trained cat and dog images and testing them using CNN model with python.
..
Ok..!
But I have one image in which both cat and dog present ...
.
Now question is how to make label cat and label ...
0
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2answers
97 views
What are Machine learning model characteristics? [closed]
This question I have received in some Machine Learning related interview and Here is the question
What questions would you ask to learn about machine learning model characteristics?
This is what ...
0
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2answers
25 views
Predicting missing data. Looking for good data predicting technique
I am analysing data for Countries Trade GDP. Some of the countries have missing GDP value for given a year. However, I have Grand Total for the entire region for that year. Is there a good data ...
0
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1answer
22 views
error while running lasso.py
The following is the error code generated while running lasso.py.
Can anybody help in fixing the same.
Here is the code:
...
0
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0answers
25 views
Which industry has more interesting use cases and more room to learn for Data Scientist, between Retail and Banking?
I am posing this question here due to the active community of Data Scientist and people with real industry experience here. I did not put in career advice because here is where we have real Data ...
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0answers
39 views
how to perform anomaly detection on industrial machine's sensor data?
I've two types of datasets, training(when machine working under normal conditions without any fault) with multiple sensor data(features) and test dataset(contains some of anomalous data). I want to ...
-2
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1answer
16 views
Converting int list to vector list
I want to train a text classifier using OnevsRestClassifier, but have problem getting a propper y. Currenly my y is a list of int, but I need it as a list of vectors.
My y:
...
0
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0answers
13 views
Cross-validation in r
I have a categorical predictor with 4 categories, 1st and last category have enough frequency but 2nd and 3rd category, each have only 2 observation, also i have binary response variable. How to split ...
0
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0answers
28 views
LogesticRegression fit() function is throwing this error
i'm following datacamp pyspark tutorial series and on chapter 04 Model tuning and selection in fitting the model, I'm getting this error when i execute these line
...
-1
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1answer
21 views
Clustering Customers on transactional behavior
Objective:
Segment the accounts on their transactional behavior and find the accounts which are more likely to subscribe for loans.
Dataset:
1) Account_Number
2-91) Transaction amount ...
0
votes
1answer
19 views
Which model can solve the “sequence demand” problem?
I have a regression problem. When a truck comes, it influences the demand of employees for the next 30 days. Additionally the demand depends on the type of truck (when the truck is big, we need more ...
2
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1answer
25 views
Adding recommendations to the output of a classification model
I have built a binary classification model using:
logit
decision trees
random forest
bagging classifier
gradientboost
xgboost
adaboost
I have evaluated the above models and chose xgboost based on ...
0
votes
1answer
61 views
How to interpret partial dependence interaction plot for binary classification?
The plot below is an example from pdpbox library https://github.com/SauceCat/PDPbox/blob/master/tutorials/pdpbox_binary_classification.ipynb. The what does 0.900 color saturation to the right mean ...
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0answers
44 views
Solving correlation and covariance with MySQL
I am new to data science taking my first course in Data analysis. I am trying to figure out where to start with a problem solving the correlation and covariance with my sql.
...
0
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1answer
31 views
Print the prediction of convolutional neural network
I have designed a convolutional neural network using tensorflow which looks as follows
...
1
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2answers
94 views
How to model & predict user activity/presence time in a website
I need to make a prediction model based on some historical data from a website's user login system. Suppose my dataset has some features like user login time and logout time for each day for a ...
1
vote
1answer
49 views
What the good general regression technqiue for a problem with 50 independent varaibles [closed]
I am a newbie to data science and statistics. I came across this problem, which has 50 independent variables and one dependent variable and trying to identify the good regression technique to start ...
1
vote
1answer
33 views
How to speed up passing of images to a GPU
I am using Ubuntu 16.04 LTS installed on a 4TB HDD. I am working with a large dataset (more than 30 GB and 150,000 images). I have a single 11GB GTX 1080 Ti GPU card on my system. I am training a mask ...
0
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0answers
20 views
Distribution of Features
I am using a dataset. The aim is to predict the average monthly loss to the company. With feature enginnering I have introduced a feature loss using workload(given per day) and the absence (given per ...
0
votes
1answer
86 views
Feature Scaling both training and test data
It is said that for:
Feature Normalization -
The test set must use identical scaling to the training set.
And the point given is that:
Do not scale the training and test sets using different ...
3
votes
2answers
87 views
How can we use Neural Networks for Decision Making intead of Bayesian networks or Desicion Trees?
I am working on Decision Making in Self driving cars and I am wondering how I can use Neural networks (is there any type) ? that can repleace or mimic the bayesian networks or Decision Tree for ...
0
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1answer
87 views
Alternatives to doc2vec?
What are some alternatives to the doc2vec embedding model? I.e models that convert paragraphs/documents into vectors, not just models that take the mean/sum of the word embeddings of each word in the ...
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0answers
17 views
EDA : Model decision making
I am working on this dataset. Completely new to the machine learning. It seems to be a time series data.
1) Can I go for regression or classification modelling for this dataset? The target id in ...
0
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1answer
31 views
Generating a set of different scenarios based on some initial observations
I have a in my hands 3 different time series which model 3 different scenarios (base, downside, upside). Every of this time-series depends on a set of 11 different attributes, which take values for ...
0
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2answers
570 views
How to create a simple K-Means Cluster Algorithm in Python? [closed]
Hi I am new to Data Science and Python.
I want to implement K-Means Cluster Algorithm.
I am successfully implemented K-means algorithm on Array of elements.
For this I did like
# K-Means.py
...
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1answer
46 views
0
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1answer
62 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 ...
3
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0answers
29 views
Differences between big data, data warehousing, business intelligence and data science?
I know they are four different áreas, but I would like to know what are the main differences between those disciplines, and how are them related to each other, if some of them depends of another, and ...
2
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2answers
72 views
2
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0answers
31 views
detecting anomaly from cdr data
I need to find anomalies from this. The term anomaly in my case is in which square id and in which time the total activity goes higher, how can I detect anomalies with the help of machine learning ...
1
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2answers
70 views
huge doubt on anomaly detection
from the naked eye itself, we can tell in the region 5161 the network usage is high so that is the anomaly in my case, then why do we want to apply k-means and other machine learning algorithms to ...
2
votes
1answer
177 views
Python - Predicting data based on multidimensional array with Keras
I've a list of data which is so called 3D array. Each of 10350 rows contains a 2D matrix with size of 150x16 (elements are float) (x_train). Corresponding training data for this huge array a linear ...
-2
votes
1answer
119 views
Which algorithms are the best choices for my binary classification problem? [closed]
Which algorithms are the best choices for my binary classification problem?
I have approximately 200 K samples in the training set and 18 attributes, including binary, numeric and categorical.
I ...
1
vote
1answer
69 views
Capturing movement importance - logistic regression output
I'm studying some event for a set of objects that can be plotted on a square $[0, 100] ^ 2$. I have used logistic regression to calculate probabilities that event occur for different objects and the ...
1
vote
3answers
45 views
Data aggregation and split train test samples
I'm working on a data science project where the goal is to predict daily electricity consumption of a building based on some of its characteristics (e.g., size, location, etc.) and weather features (e....
6
votes
2answers
75 views
Is there any consensus on choosing an appropriate ML approach?
I am studying data science at the moment and we are taught a dizzying variety of basic regression/classification techniques (linear, logistic, trees, splines, ANN, SVM, MARS, and so on....), along ...
