Questions tagged [machine-learning]

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

Filter by
Sorted by
Tagged with
1
vote
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 ...
0
votes
0answers
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 ...
1
vote
2answers
76 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 ...
1
vote
1answer
21 views

some algorithms to identify of a pattern in text data

I have few sentences like below in my project(around 25000), ...
0
votes
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 ...
0
votes
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 ...
1
vote
0answers
32 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 ...
0
votes
0answers
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 ...
0
votes
1answer
28 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 ...
1
vote
1answer
36 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 ...
0
votes
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 ...
0
votes
3answers
53 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 ...
-1
votes
1answer
14 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, ...
0
votes
0answers
32 views

When and how tensorflow uses certain underlying operations?

I have two sets of networks: network1: ...
1
vote
1answer
21 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 ...
3
votes
2answers
131 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 ...
1
vote
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 ...
0
votes
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 ...
0
votes
1answer
23 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 ...
0
votes
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 ...
3
votes
0answers
74 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 ...
1
vote
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 ...
1
vote
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 ...
0
votes
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 ...
0
votes
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 ...
1
vote
1answer
29 views

Probability calibration is worsening my model performance

I'm using RandomForest and XGBoost for binary classification, and my task is to predict probabilities for each class. Since tree-based models are bad with outputting usable probabilities, i imported ...
0
votes
1answer
21 views

CART algorithm (Classification and regression trees) question

So this is taken from an exam I just did. I'd like to know if there are any instances same as in the image where the CART algorithm could use a negative alpha and thus encourage a larger tree? Or does ...
2
votes
1answer
18 views

incremental learning vs transfer learning

Can anyone explain me how incremental learning differs from transfer learning with example? Also does Transfer learning limited to neural networks?
0
votes
1answer
26 views

What machine learning algorithm should I use for specific user configuration?

I have a data-set that contains thousands of employee data, including their role, department (Applications Developer, IT Support, Network Management etc.), and using one-hot encoding all of the ...
1
vote
2answers
50 views

Correlation vs Multicollinearity

I have been taught to check correlation matrix before going for any algorithm. I have a few questions around the same: Pearson Correlation is for numerical variables only. What if we have to check ...
1
vote
0answers
12 views

What are the 'easier' option for LSTM?

I am currently working on rare event prediction, which I have never done before (I used to work with simple prediction problem), and I looked up on this article about using LSTM for time series rare ...
1
vote
0answers
29 views

Class imbalance [closed]

I am working on a project with high binary class imbalance. I've tried other methods such as class weight and using an ensemble, but I want to try out a third: upsampling. Is it ideal to upsample ...
0
votes
0answers
15 views

Predicting which customers will switch brands

I wish to predict which customers will move between products (A to B) when product A is no longer available for purchasing due to restrictions we have made. Product B is equivalent to Product A and is ...
1
vote
1answer
25 views

Multivariate time series prediction with binary target

I have an electronic component whose sensors record temperature, current and voltage values of various sub-elements. These readings are taken at regular intervals of time and I organized them as ...
0
votes
0answers
13 views

Models to classify data based on different properties

I have a problem that I am trying to solve. I have some time series data, say monthly sales over the past 20 years. I have this information for each customer in a store, there are 10,000 customers (...
0
votes
0answers
12 views

supervised similarity scoring system - recommender system

I have a dataset of movie collections with 10-15 features describing each movie. I also have a dataset of user ratings of the similarity between some random pairs of movies. Using both of these data ...
0
votes
1answer
17 views

Algorithm for user profiling without distinct profiles

I am trying to design an algorithm that takes in a new user with the variables department, location, job_role etc. and I want a machine-learning algorithm to decide ...
0
votes
2answers
24 views

Comparing two time series data to find deviations between them [closed]

This is a use case that I have and I am trying to automate this. Any pointers would be helpful. Use Case: When we deploy any new version of a web service, we keep monitoring it (while deploying to ...
0
votes
0answers
20 views

Upload 'tsv' file to Google Colab / Jupyter Notebook

TSV(Tab separated Value) extension file can't be uploaded to google colab using pandas Used this to upload my file ...
2
votes
1answer
18 views

Understanding the multidimensional-nature of the data being fed to a RNN and its output

Assuming we have a time-series dataset whose window_size = 30 and the batch_size = 4, which makes the overall input = 4*30 (2D). But as RNN expects 3D input, ...
2
votes
2answers
59 views

Why should I know C++ ,if I am a machine learning engineer?

I see there's a lot of machine learning job openings with skills requirements, python ,R, keras,tensorflow,pytorch,spark, etc.which are completely fine & reasonable, but why many of the recruiters ...
2
votes
1answer
21 views

Bi-directionality in BERT model

I am reading the paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding that can be found here. It looks to me that the crux of the paper is using masked inputs to ...
1
vote
1answer
18 views

when to use certain metrics for splitting decision trees?

So I just very recently learned about decision trees, and the different metrics for determining the best split when training the tree. I cannot seem to be able to find anything on which metric to use ...
0
votes
1answer
24 views

Feature selection before or after applying filter in Time-series forecasting

I'm predicting ozone concentration based on meteorological variables and ozone value of the previous day. I applied savitzky golay filter to get rid of noise in the time-series dataset. My question ...
1
vote
1answer
30 views

Linear Discriminant - Least Squares Classification Bishop 4.1.3

Pls. refer section 4.1.3 in Pattern Recognition - Bishop: "Least squares for Classification": In a 2 class Linear Discriminat system, we classified vector $\mathbf{x}$ as $\mathcal{C}_1$ if y($\bf{x}...
2
votes
1answer
24 views

Are batch iteration and epochs different in reinforcement learning compared to supervised learning?

I'm following the Udacity "AWS DeepRacer" course about self driving cars with reinforcement learning. In one lesson, they says this: Batch size - This determines how many images, randomly sampled ...
2
votes
0answers
20 views

Using deep-learning on graph data for binary classification

The data: I have certain data that I decided to represent it as a graph (I thought it would suit). So I have the weighted graph data that includes a numeric attribute for each node. (networkx graphs)....
0
votes
0answers
19 views

Keras - Deal with inputs of 2 different shapes

I'm trying to make a model that deals with categorical data of the shape (891,4,20) and numerical data of the shape (891,4). To explain further, the categorical data has 891 sequences, 4 different ...
0
votes
0answers
25 views

reverse engineer console game FPS sensitivity for replication

Would it be possible to reverse engineer a FPS games sensitivity/dead zone/acceleration curve/ and other data by recording the games screen and running a controller through a pc to record joystick ...