Questions tagged [machine-learning]

Methods and principles of building "computer systems that automatically improve with experience."

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17 views

can i make model that can take N shape input?

as far as i try all data that model take are fixed size or fixed shape, i had problem that i give data to model but it has no fixed shape and i can not cut part of it as all of it are important,so can ...
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15 views

what is the good feature? [closed]

Just wonder that what is the good feature for data analysis. for linear regression, the correlated feature will be important but for other models it probably not How you will be answering to the ...
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2answers
59 views

What is the best way to approach this problem? [closed]

I'm new with data science, but I'm familiar with python3. I'd like to solve a problem with machine learning, but I'm totally new to this field, which is why I am looking for someone kind enough to ...
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8 views

How to handle optimization problem when objective function and constraints involve different set of parameters

I am working on this constrained optimization problem. The objective function is the efficiency of the machine which is determined by 6 controllable variables. The constraint is the pressure can't ...
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1answer
26 views

Implementing Mahalanobis Distance in Python

I am trying to implementing Mahalanobis Distance from scratch but I am getting an error- The formula for Mahalanobis Distance is- Now my code is- ...
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0answers
11 views

How should i prepare my dataset for efficient object detection and multi class classification?

I am currently using faster RCNN inception v2 model for detection and classification of object of 2 different type which are very closely identical (eg. rip apple and partially stall apple). how ...
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33 views

What does big O mean in KNN optimal weights?

Wiki gives this definition of KNN In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression. In both cases, the input ...
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1answer
30 views

Forecasting multiple time series with a single model

I have a dataset with sales numbers for ~500 different markets (assume different cities or regions) and need monthly forecasts for each market. Instead of building 500 different models, I'm interested ...
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1answer
9 views

Appropriate model metric for a truncated response variable?

Here's a straightforward question I can't seem to find a good answer to. Let's say you're using some variables to predict age. I'm assuming a regression model is the right approach. In this case, what ...
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32 views

How multi layer LSTM are interconnected?

I am trying to understand the layers in LSTM for my own implementation using Python. I started with Keras to getting familiarized with the layer flow. I have tried the below code in Keras and I have ...
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1answer
13 views

How does PCA and clustering treat different type of predictors where order of their values signify the result differently?

Assume we have 3 variables for 3 countries as shown below: ...
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1answer
17 views

SelectKBest and Correlation returns me excatly same feature selection. How?

Im working on selecting most effective features from a dataset with over that 2000 features. Im using different algorithms for that (selectKBest with chi-square, Extra Trees, Correlation etc.) But ...
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16 views

Algorithm for Calculating average feature usage

We arr trying to develop an algorithm to calculate the average usage of a feature on a website. e.g. usage of search button on google page. Approach 1- Average usage = count of feature use/ count of ...
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1answer
16 views

Very simple real-valued time-series dataset for RNN prototyping

Is there a simple real-valued time-series dataset on which a vanilla RNN model can be trained. With "very simple" I mean only two to four real-valued inputs per time step and a single real-valued ...
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1answer
21 views

How is the cross-product transformation defined for binary features?

I am reading the paper on Wide & Deep learning and for the wide component, it states that one of the most important transformations is the cross-product transformation. This is defined as follows: ...
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7 views

what are possible error analysis approach in tabular data?

I am working on binary classification on tabular data. The dataset is mostly made of categorical data and after fitting the data to a model I found test accuracy to be low. I want to do error analysis ...
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1answer
33 views

Anomaly Detection in Time Series: How to label the data

How to label time series so that we can train it on machine learning models to classify data point as anomaly or not? If I have time series, and anomaly occurs at time t, should I label that point 1 ...
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1answer
22 views

R package vs REST API

I have a logistic regression algorithm in R to predict irresponsible users. I need this to be as flexible as possible for any market. I would need to use the logistic regression algorithm to ...
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13 views

For time series forecasting task, should I use data across several time steps or singe timing data for prediction?

I have a time series forecasting project, there are over 10, 000 time steps of data, so the data amount is not a problem. At first, I thought I've to create a time-based data pipeline that forms the ...
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11 views

How to backpropogate error from convolutional layer with respect to the input when using multiple channels

I have been attempting to implement a Convolutional Neural Network in python and have run into a bit of a roadblock. When backpropogating the error in a convolutional layer let us say that we receive ...
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4 views

Getting error while using label encoder class

So , thing is I was working on titanic dataset . During data preprocessing when i tried to use LabelEncoder I got the following error. Here X contains the train set while X1 contains the test set. As ...
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1answer
19 views

Image's pixel data readability for ML [closed]

So I have a python program that lets me draw on a 250x250 pixel canvas. I save the images as .png, then convert them to .csv (the value of a pixel can be either 0 or 255). At the moment, I get this: ...
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2answers
30 views

ScikitLearn - RandomForestRegressor score different in and out of grid search

I am using RandomForestRegressor (scikit-learn python package). I am looking for the best values for hyperparameters ...
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6 views

3D plot and its 2D projection for two classes

I am unable to plot 3D plot from the points in 3 dimension properly using scipy multivariate_normal and matplotlib.Attaching the question and the code I wrote: Question: Create samples in 3 ...
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2answers
72 views

Using random forest for selecting variables returns the entire dataframe

I am in the process of dimensionality reduction. I am using Random Forest to find the columns with the highest level of correlation with the target SalePrice column. The problem is that the output ...
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1answer
21 views

some algorithms to identify of a pattern in text data

I have few sentences like below in my project(around 25000), ...
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1answer
27 views

Regression methods [closed]

I want to understand what regression methods exist and their purpose. I know the least squares method with which you can build a linear and non-linear model and make predictions. The ARMA model is ...
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0answers
19 views

Setting Up Training Data to Perform Image classification

I want to use Orange for an Image Classification project I am working on. I have a training image set and separate .csv with columns corresponding to the image (by name) and classifier. Wondering ...
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0answers
31 views

Which one is better for handling spatio-temporal data: 3D CNN vs 2D Recurrent CNN?

Please forgive my ignorance and lack of experience: I am asking this question seeking answer from the experts/experienced persons in the field. I have a training dataset where each sample is a 3D ...
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3 views

Approach recommendation to enhance time step determination in dynamic simulation

I am developing a specialized tool to perform dynamic simulations of a specific family of physical systems. This tool has two major parts: establishing the kinetics, and deciding how far into the ...
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1answer
27 views

How to predict the value in KNN?

I am trying to build the KNN algorithm for IRIS dataset. First, I've computed the distance and stored it in 1d array. However, I am really struggling to build the prediction function. Therefore two ...
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1answer
35 views

Best approach for a simple self driving car

I'm planning to build a small car with autonomous driving (maybe modifying my current rc car or using a robot car kit, using arduino and raspberry). I'll use a CNN, and I'm thinking how to collect ...
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27 views

Sequential pattern mining on system error logs (time series, no transactions) [closed]

To preface, I am a newbie. I've done some NLP before, but I am pretty inexperienced in terms of data science. I have a set of system error logs. Each line has a timestamp, and an error message (there ...
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1answer
36 views

How to input a 3d model into ML algorithm?

I have a machine learning model that uses csv with measured data about buildings: width, length, height etc. I use it to predict some features and it works properly. I would like to drop csv with ...
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3answers
52 views

what are effects of working with categorical dataset

I am working on classification problem where the dataset contains 90% of features as categorical. It is binary classification problem, and the class is heavily imbalanced. I performed Smote over ...
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1answer
13 views

What is a color blob? Is it possible to use clustering algorithm to color blob detection problem?

Wiki gives this definition of blob detection In computer vision, blob detection methods are aimed at detecting regions in a digital image that differ in properties, such as brightness or color, ...
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32 views

When and how tensorflow uses certain underlying operations?

I have two sets of networks: network1: ...
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1answer
19 views

Why do we divide the regularization term by the number of examples in regularized logistic regression?

So this is the formula for the regularized logistic regression cost function: $x^{(i)}$ - the $i$'th training example $\theta_j$ - the parameter of the $j$'th feature $m$ - the number of training ...
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2answers
127 views

Why use regularization instead of decreasing the model

Regularization is used to decrease the capacity of a machine learning model to avoid overfitting. Why don't we just use a model with less capacity (e.g. decrease the number of layers). This would also ...
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0answers
14 views

How mAP is unfair evaluation metric for Object Detection?

The following figure is from the last page in YOLOv3 paper highlighting how mAP is unfair metric for evaluating Object Detectors: The figure shows two hypothetical Object Detector results which the ...
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1answer
25 views

Training a model for fall detection

My parents are elderly and a fall is a BIG DEAL. I'm pretty good at coding and such. So I thought I'd use some fall datasets and plug them into a machine learning system. As you can see from this ...
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1answer
21 views

Adding machine learning classifier at the end of CNN layer

I wanted to use the CNN as feature extractor for my images and then fed these features to some machine learning classifiers such as SVM, decision tree and KNN. However when I was trying with SVM I got ...
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0answers
19 views

Getting Different Class output and Probability when predicting from model.predict and after deploying model with flask

For Binary classification problem,I am getting Different Class output and Probability for test data when predicting from model.predict and with deployed model with flask. In model.predict I am getting ...
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0answers
9 views

what is the process of Feature store reusability? [closed]

Currently in our organisation we have a feature store where in we do create feature query which query main tables or facts which is in hive for training data. However that creates lot of issue in ...
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0answers
72 views

Why is training and validation loss steadily rising (eventually to NaN) in this CNN of mine?

Dear ML and data scientists: I have 4 layers of gray scale images for every single biological specimen in my dataset. I am trying to train a 4-convolution CNN (see pytorch architecture below) to ...
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2answers
16 views

ConvNet with concatenated data

I have a basic question regarding convolutional neural network. Assume I have a set of 1000 RGB images and I train a CNN from this set. I can obviously split each of my RGB images into 3 different ...
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1answer
31 views

How to Improve Low Accuracy Keras Model Design?

I am trying to train a system that looks at some data points and predicts the quantity of surfers on a surf break. I have labeled the pattern for the past 2 months and I have 1500+ training examples ...
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1answer
22 views

What is the best way to optimize the parameters in a Sklearn classifier, when I have little data?

What is the best way to optimize the parameters in a Sklearn classifier when I only have a data set with 684 rows and 177 columns, and the column I want to predict has 3 labels? I know I should split ...
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0answers
16 views

Feature selection for circular data in time-series

I'm predicting ozone concentration based on meteorological and seasonal variables. In the feature engineering stage I converted the MONTH, DAY_OF_WEEK, DAY_OF_YEAR to its sin and cosine components ...