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H: Probabilities of a Poisson distribution not making sense
I am trying to find probabilities of orders a restaurant gets on Sunday's. For last 6 months average orders are 1000 without any big anomalies like 700 or 1300. This is a case of poisson distribution & I used scipy library in python and plotted the probabilit... |
H: Linear regression compute theta
I'm trying to compute the theta for a regression linear exercice.
x = x * 1.0
y = y * 1.0
# add ones
X = np.ones((201, 2))
X[:, 1] = x
# convert to matrix
Y = y[:,np.newaxis]
# compute teta
p1 = (X.dot(X.T))**-1
p2 = (X.T).dot(Y)
theta = p1.dot(p2)
The last line failed with erro... |
H: Difference between Non linear regression vs Polynomial regression
I have been reading a couple of articles regarding polynomial regression vs non-linear regression, but they say that both are a different concept. I mean when you say polynomial regression, in fact, it implies that its Nonlinear right. Then why there... |
H: Prevent overfitting when decreasing model complexity is not possible
I'm fairly new to machine learning and as an exercise for a more complicated task, I'm trying to do the following what I thought was a trivial task. Suppose as an input I have population density maps. These are 2D images with one layer, in which e... |
H: Tensorflow error: Input signature not matching inputs
I've been following Sentdex's tutorials on YouTube about Deep Learning and I've encountered and error while trying to load an image and run it through the model. The error says that the inputs do not match the input signature but I've been struggling to find out... |
H: Process of solving a problem using ML
newbie here. I finished a couple of online courses and read Intro to Statistical Learning, thinking of working on a personal project and would appreciate it if you can clarify some issues:
What does "cleaning" the data consists of? How do you know if your data needs cleaning a... |
H: Does resizing images during training affect the bounding box annotations?
I am using the TensorFlow object detection API to train my own custom dataset and am preparing annotations for the same. I see from the config file of my pre-trained SSD inception net, the size of the image is reduced to 300 x 300 during trai... |
H: Combining multiple neural networks with different activation functions
I have 3 neural networks where each has as a different activation function: Sigmoid, Tanh and Softmax. I am planning to average their final predictions, but as we know the functions doesn't have the same range values.
P = (P1 + P2 + P3)/3
Whe... |
H: Difference between Gensim word2vec and keras Embedding layer
I used the gensim word2vec package and Keras Embedding layer for various different projects. Then I realize they seem to do the same thing, they all try to convert a word into a feature vector.
Am I understanding this properly? What exactly is the differe... |
H: Get Logistic regression scores in CNN using Keras
from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras import backend as K
from keras.regulariz... |
H: Valid actions in OpenAI Gym
Why don't the gym environments come with "valid actions"? The normal gym environment accepts as input any action, even if it's not even possible.
Is this a normal thing in reinforcement learning? Do the models really have to learn what valid actions are all the time? Would it not be muc... |
H: Dealing with input images of different shapes in PyTorch
I've started to work with a leaf classification dataset on Kaggle. All input images have different rectangular shapes. I want to transform the input into squares of a fixed size (say, 224x224) with a symmetric zero-padding either on top and bottom or on the l... |
H: Why compressed image size is greater than original one in kmeans algorithm?
I have a png image as shown below.
And I use kmeans algorithm to compress the image by color quantization. I compressed the image to use 64 colours. The code is:
ncolor = 64
rimage = image.reshape(image.shape[0]*image.shape[1],3)
kmeans = ... |
H: Can I save only some VGG19's layers into a .H5 file?
I am training a deep-learning style transfer model with the pretrained-VGG19 CNN.
My aim is to use it in my Android app for personal purposes with Google Firebase Machine Learning Kit (which would host my .H5 model to make it usable by my Android app). The maximu... |
H: can I use z-score normalization even if it doesn't make sense for my data to be negative?
I'm planning to use z-score as a Normalization Method for a Project but I noticed if I do that then I ll have a data in the range [-1, 1] which is wierd because I have data that doesn't make sense for it to have negative value... |
H: Multilayer Perceptron: What is the value used to update the weights in the hidden layers?
As i understand for the output layer the error rate is used with the mean squared error function to update the weights.
For the hidden layers as well? Does that make sense?
AI: A Multilayer Perceptron changes your weights by a... |
H: Error rate of AdaBoost weak learner always bigger than 0.5?
As far as i understand, weak learners of AdaBoost should never yield a error rate > 0.5
After training one, i only receive error rates above 0.5. How is that even possible? The AdaBoost Tree still gives quite good results, but all learners weights should b... |
H: When would not normalizing input values have higher accuracy?
Right now I'm training a deep neural network for a binary classification problem, with a feature set of winrates. As such, each winrate is bigger or equal to 0 but smaller than 100.
I've been getting promising results without normalizing the input data, ... |
H: When using Absolute Error in Gradient Descent, how to calculate the derivative?
What is the derivative of the Loss Function (Absolute Error) with respect to the feature weights that is used to update the weights?
Couldn't find anything specific about it anywhere.
AI: The gradient of MAE is not continuous in $y_{pre... |
H: Is it common to add noise to Time Series data before training a model
I once read about somebody who added noise to their time series before training a model. They didn't write why they did it though.
Is this common practice?
If it is, why do people do it ie. to prevent over-fitting?
AI: I'll go through your quest... |
H: How does XGBoost use softmax as an objective function?
I'm quite used to seeing functions like log-loss, RMSE, cross entropy as objective functions and it's easy to imagine why minimizing these would give us the best model. What's difficult to imagine is how XGBoost uses softmax, a function used to normalize the lo... |
H: Where to get the Datascience Use cases for practice
I just started learning data science. I have gone through some of the courses in coursera & udemy, now i want to practice what i have learned. What i want to know is from where can i get the Use cases (linear regression & multiple linear regression) so that i cou... |
H: Combining text (NLP), numeric, and categorical data for a regression problem
I have a dataset
data = {
points: 3.765,
review: `Food was great, staff was friendly`,
country: 'Chile',
designation: 'random',
age: 20
}
I am looking for a way to use these features to build a model to predict po... |
H: Bagging vs Boosting, Bias vs Variance, Depth of trees
I understand the main principle of bagging and boosting for classification and regression trees. My doubts are about the optimization of the hyperparameters, especially the depth of the trees
First question: why we are supposed to use weak learners for boosting... |
H: Best framework for recognizing a specific cartoon character's face?
I have a supply of images of a specific cartoon character's face. I have hours of video. I would like to automatically find the sections of the video in which this cartoon character appears.
https://github.com/ageitgey/face_recognition doesn't seem... |
H: What to do after GridSearchCV()?
I happily created my first NN and performed hyperparameter optimization through GridSearchCV. I just don't know what to do next.
Do I have to fit it again with the best parameters GridSearchCV() revealed? is there an elegant way to do so?
Otherwise, how to proceed?
def create_model(... |
H: Validation generator in Autoencoder returning NaN
I am trying to build a fairly simple autoencoder using Keras on the OpenImages dataset. Here is the architecture of the ae:
Layer (type) Output Shape Param #
=================================================================
conv3d... |
H: Medical Image Analysis
What are some good starting points for learning medical image analysis and combining it with deep learning?
I would like to analyze images with bone cancers but not sure what is proper way to preprocess them and prepare for the model.
AI: Check out this blog post. There you find a summary of ... |
H: Numpy arithmetic operation between two columns
Below is the numpy array. I need to perform two operations on this array.
Add one column with value [column 1] - [column 3].
Add another column with value [column 1] - [previous value of column1].
I can do this using normal list operations, but is it possible to use ... |
H: Difference between validation and prediction
As a follow-up to Validate via predict() or via fit()? I wonder about the difference between validation and prediction.
To keep it simple, I will refer to train, val and test:
Training data: Train model, especially find hyperparameters through GridSearchCV or similar
Va... |
H: Finding Criminal Name in news?
We have news URLS, which we want to classify into crimes or non-crimes and further identify criminals by using NERs.
For creating a model that identifies criminals, we tried SPacy which gave all the names like lawyers name , president ,criminal etc..
can Anyone help on how to get on... |
H: Transfer learning VGG16 does not work as expected. (Detect tacos as hamburgers)
I am new in this field of machine learning, to test I wanted to do a simple project. Create a cnn capable of recognizing hamburger images. As I do not have the ability to collect more than 10,000 images of hamburgers I have used an exis... |
H: How prevalent is `C/C++` in machine learning development?
I am currently a data scientist mostly doing NLP, and I do most of my work inPython. Since I didn't get a CS degree in undergrad, I've been limited to very high level languages; Java, Python, and R. I somehow even took Data Structures and Algorithms avoiding... |
H: Why is word prediction an obsession in Natural Language Processing?
I have heard how great BERT is at masked word prediction, i.e. predicting a missing word from a sentence.
In a Medium post about BERT, it says:
The basic task of a language model is to predict words in a blank, or it predicts the probability that ... |
H: Explaining feature_importances_ in Scikit Learn RandomForestRegressor
For a project, I used the feature_importances_ attributes from the RandomForestRegressor. Everything works well but I don't know how to explain why one feature is more important than another. I mean I know that the higher the score is the higher... |
H: Extracting MM-YYYY from python date and creating a new column with the same
I want to extract the month and year from one of my date columns in the dataset and create a new column in the data-frame with the new MM-YYY format.
My current solution is working fine but its way to long. I am looking for an efficient wa... |
H: Suggestion for stacked modelling in machine learning
I have built several models on the training dataset and i am not happy with the results and I wish to club them all together and generate a new model, so here is my idea as i already have the results for the existing models i would like to create a new dataset wi... |
H: What is the meaning of "probability distribution of p(x)" of something uncountable?
I'm studying VAE and new to both of the neural network and the statistic.
After some researches, I could understand the rough concept of VAE.
But what makes me confused is, the meaning of probability distribution p(x) itself.
When t... |
H: How to print nullity correlation matrix
I've a trainingset which has 400 features and most of them have null value.
I tried to draw the heatmap of nullity correlation matrix by means of Python and missingno, but the heatmap is unreadable due to high number of features.
How can I print the nullity correlation matri... |
H: Why does removal of some features improve the performance of random forests on some occasions?
I completed feature importance of a random forest model. I removed the bottom 4 features out of 17 features. The model performance actually improved. Shouldn't the performance degrade after removal of some features, given... |
H: AttributeError: 'str' object has no attribute 'month' Process finished with exit code 1
Python code
import pandas as pd import numpy as np import os
RD = pd.read_csv("C:/Users/acharbha/Desktop/fullbackup_success/python/raw_Data_success_Rate.csv")
NEW = {"Cell": RD['Cell'], "LastFullResult": RD["LastFullResult"], ... |
H: When do you use FunctionTransformer instead of .apply()?
I'm watching a PyData talk from 2017 in which the speaker provides this example for how to use FunctionTransformer for sklearn.preprocessing
from sklearn.preprocessing import FunctionTransformer
logger = FunctionTransformer(np.log1p)
X_log = logger.transform(... |
H: Backpropagation chain rule example
My question is in regards to an MIT course example.
The instructor delves into the backpropagation of this simple NN.
I have two questions.
Why do we seem to disregard the weights of the second layer (in blue)?
The red circle, should this not be $\partial y_2$ (followed by $... |
H: Help in understanding the maths behind Logistic Regression
I am following the lecture notes available https://www.stat.cmu.edu/~cshalizi/uADA/12/lectures/ch12.pdf
I cannot understand how Eqs 12.4 and 12.5 come,
why the Bernoulli probability has $1-p(x)$ in the denominator,
how come $p(x) = \exp(\beta + \beta^Tx)$
... |
H: What to do with large number of collinear variables?
I have this time-series dataset that has 63 features, out of which 57 were manually engineered. While checking for collinearity, I get this correlation matrix:
As can be seen there are a number of variables that are correlated/collinear. The ones that are deep r... |
H: Normalize / Standardize in a Random Forest?
If I have a matrix of co-occurring words in conversations of different lengths, is it appropriate to standardize / normalize the data prior to training?
My matrix is set up as follows: one row per two-person conversation, and columns are the words that co-occur between s... |
H: cross validation issues
I have come here from this great answer. I have come across many approaches for using cross validation and the answer to the attached question is by far explaining it the best to me. My dilemma is that now that I m not able to figure out what to use Kfold cross validation for:-
Testing over... |
H: Feature engineering - house price prediction (small dataset)
I am working on the task of predicting real estate prices. My dataset has only 10 variables described below. I'm thinking about feature engineering but nothing comes to mind.
Variables:
street
city
zip code
rooms
bathrooms
square feet
type
price
latitude... |
H: What dataset was Stanford NER trained on?
I would like to re-train the Stanford NER library from scratch as a 1 class model.
Only 3,4 and 7 class models are available out of the box.
Is it possible to obtain the data that the model was originally trained on?
AI: The original paper mentions two corpora: CoNLL 2003 ... |
H: Same probability for all classes
I implemented a fully connected MLP of shape [783 (input), 128 (hidden layer) and 10 (output)] the hidden layer had a sigmoid activation function and the output a sofmax.
I tested with the dataset of keras: Classify images of clothing.
At first I got the ouput was 0.1 at all the exi... |
H: Intuition behind PCA eigenvectors
For undergraduate students who understand the definition of
eigenvectors and eigenvalues,
$$A v = \lambda v \;,$$
what is the intuition behind why the eigenvectors of the
covariance (or correlation) matrix correspond to the axes of maximal stretching?
Why specifically does that m... |
H: Convolutional neural networks for non image dataset
Can we use Convolutional Neural networks for a non image dataset for prediction?
The dataset is a record of student academic details
I know that CNN is mostly used in computer vision and image processing for analyzing visual imagery.
And it is also used in natura... |
H: Problem importing dataset
I am new to machine learning and I am trying to build a classifier. My problem is that I am not able to import the dataset I need. In particular, I put my dataset in the Desktop and what I did is:
#pakages
import numpy as np
import pandas as pd
import jsonlines #edit
fro... |
H: Dealing with irrelevant features in dataset (Homework)
I have a specific question pertaining to one of my machine learning homeworks.
Basically, we are required to build a model that takes a 5000*10000 dataset X (5000 examples each with 10000 features), and predict Z, which is a 5000*2 Matrix. The dataset Z is syn... |
H: How to choose a model for this cross-validation curve?
I'm using GridSearchCV to tune hyperparameters for a Logistic Regression multiclass model.
I read on Kaggle that you should choose the hyperparameter that results in the lowest discrepancy between the CV-score and the training score, but in this case this lead... |
H: Best file format for transfer of EHR data
I am working on a clinical trial where we have several sites sending us EHR data. The sites are currently sending the data in excel files. I have a feeling someone's opening the files because 3 of the files have 64,999 rows exactly, and excel 2007 cuts off at 65,000.
I a... |
H: Why Keras Dense layer is expanding number of tensors in each layer
I have following model:
and I wonder why is the number of parameters different for e.g. dense_2477 and dense_2482? Both layers have the same amount of neurons so why do they provide different parameter numbers?
AI: The number of parameters is the n... |
H: TS-SS and Cosine similarity among text documents using TF-IDF in Python
A common way of calculating the cosine similarity between text based documents is to calculate tf-idf and then calculating the linear kernel of the tf-idf matrix.
TF-IDF matrix is calculated using TfidfVectorizer().
from sklearn.feature_extract... |
H: Why is the variance going down so much in this weight initialization problem(using pytorch)?
first look at this example
>>> x = t.randn(512)
>>> w = t.randn(512, 500000)
>>> (x @ w).var()
tensor(513.9548)
it makes sense that the variance is close to 512 because each one of 500000, is a dot product of a 512 vector ... |
H: Turning Histogram values into Numerical format ( Excel-xslx, Pandas-DataFrame, etc.)
I am trying to do a correlation study about personality traits as described in Hofstede's :https://www.hofstede-insights.com/product/compare-countries/ . I would like to have the values described in the bar charts numerically into... |
H: Supported GPU for Pytorch
Question
Which GPUs are supported in Pytorch and where is the information located?
Background
Almost all articles of Pytorch + GPU are about NVIDIA. Is NVIDIA the only GPU that can be used by Pytorch? If not, which GPUs are usable and where I can find the information?
AI: That's correct, y... |
H: Square-law based RBF kernel
What is the Square-law based RBF kernel (SQ-RBF)? The definition in the table at the Wikipedia article Activation Function looks wrong, since it says
y =
1 - x^2/2 for |x| <= 1
2 - (2-x^2)/2 for 1 < |x| <= 2
0 for |x| > 2
but this makes it discontinuous a... |
H: R packages: How to access csv files in data subfolder?
I have successfully written an R package and want to ship it with a specific csv file. I placed the file in the data and data-raw subfolders.
read.csv("data/foobar.csv")
The above command fails. How can I read the csv file?
AI: data-raw is for storing data alo... |
H: Suggestions on how to explain 'models' & 'algorithms'
I guess other members of this Stack have ran in to this before, but I may be wrong: Have you ever been approached and asked to explain the difference between models and algorithms? This happened to be recently and, while I feel that I explained it well, there is... |
H: Why I am having ValueError in this Linear Regression?
from sklearn.linear_model import LinearRegression
ClosePrices = data['Close'].tolist()
OpenPrices = data['Open'].tolist()
OpenPrices = np.reshape(OpenPrices, (len(OpenPrices), 1))
ClosePrices = np.reshape(ClosePrices, (len(ClosePrices), 1))
regressor = Linea... |
H: Why are my predictions bad, if my accuracy in train is roughly 100% (Keras CNN)
In my CNN i have to handle 2 classes in a binary system, I have 700 images each class to train, and others to validation. This is my train.py:
#import tensorflow as tf
import cv2
import os
import numpy as np
from keras.layers.core impo... |
H: how to split the original data in training, validation and testing?
I have the original data but i didn't know how to split the data and how to implement that data into some algorithms. can you guys help me out in this problem.
thank you
AI: I think you should start with some tutorials to understand the cycle of a ... |
H: suggestion for good online source according to Syllabus
Hi, are there some online courses e.g. some classes in Coursera?
I have difficulty in following the professor's teaching because I have a weak statistics background. I want to catch up by reading some online complementary resource!
Thank you!
AI: A good deal ... |
H: Genetic algorithms: what connection to support vector machine / naive bayes
I found the following list of seven classifiers:
Linear Classifiers: Logistic Regression, Naive Bayes Classifier
Nearest Neighbor
Support Vector Machines
Decision Trees
Boosted Trees
Random Forest
Neural Network
What are genetic algo... |
H: Problem building a feature vector
I am trying build a classifier for malware analysis for which basing in the instructions of an assembly code, such as push, mov,... I want to predict the compiler, and in a second time the optimization op, and I am having some troubles. My code is the following:
#pakages
import num... |
H: How to Keep Missing Values in Ordinal Logistic Regression
I’m using mord package in python to do ordinal logit regression (predict response to movie rating 1-5 stars).
One of my predictor variables is also ordinal but there are some missing values where the viewer skipped a question because it wasn’t applicable due... |
H: Deep Learning for non-continuous dataset
I am working with this dataset which is record of student academic details and I want to predict the student's performance.
since the dataset is non-continuous I cannot apply CNN on this dataset.
How can I apply Deep learning on this kind(non-continuous) of dataset. I search... |
H: Genetic algorithms(GAs): to be considered only as optimization algorithms? Are GAs used in machine learning any way?
As a quick question, what are genetic algorithms meant to be used for? I read somewhere else that they should be used as optimization algorithms (similar to the way we use gradient descent to optimiz... |
H: Difference between learning_curve and validation_curve
What is the difference between these two curves: learning_curve and validation_curve ?
AI: Both curves show the training and validation scores of an estimator on the y-axis.
A learning curve plots the score over varying numbers of training samples, while a vali... |
H: How to fine tuning VGG16 with my own layers
I want to maintain the first 4 layers of vgg 16 and add the last layer. I have this example:
vgg16_model = VGG16(weights="imagenet", include_top=True)
# (2) remove the top layer
base_model = Model(input=vgg16_model.input,
output=vgg16_model.get_layer(... |
H: Anomaly detection thresholds issue
I'm working on an anomaly detection development in Python.
More in details, I need to analysed timeseries in order to check if anomalies are present.
An anomalous value is typically a peak, so a value very high or very low compared to other values.
The main idea is to predict tim... |
H: Grid search or gradient descent?
Assume we have a neural network and one of its activation functions is a function of parameter a. We want to find the weights and parameter a that leads to the minimum loss on the validation set which one is better?:
Treat a as a hyperparameter. Do grid search for a: consider a ... |
H: Back-propagation and stochastic gradient descent
Is backpropagation a learning method or an optimisation method?
How are backpropagation and stochastic gradient descent related to each other?
AI: Stochastic Gradient Descent (SGD) is an optimization method. As the name suggests, it depends on the gradient of the opt... |
H: LSTM fot text classification always returns the same results
Hello fellow Data Scientists,
I'm trying to make a classifier that was to classify sequences of text into some predefined classes, but i always get the same output, can anyone help me understand why?
The training of the model:
# The maximum number of w... |
H: Building an efficient feature vector
I am building a classifier for malware analysis, which predicts if I have a malware by looking at the intructions of an assembly code, such as push, mov,... and predicting the optimization method. Note that I am considering a json file. My code is the following:
#pakages
import... |
H: Frequency of occurrence - dummy variables
I am thinking about it not the first time, namely if I have a variable that I want to convert later to the variable dummy (cities in this case), should I delete lines that occur less often than N times?
For example, the value of new york has occurred 400+ times but there ar... |
H: What expresses if/how two variables are dependent on each other?
The accepted answer to question Why is a correlation matrix symmetric? includes this:
The correlation matrix is a measure of linearity. It does not express how two variables are dependent on each other.
My question is : What is there that is relate... |
H: Is (manual) feature extraction outdated?
I recently attended a PhD thesis defence in which one committee members claimed that "manual feature extraction is outdated. Nowadays, we have [deep] machine learning models doing that job for us automatically."
Is this statement true? If yes, please provide a reference subs... |
H: How can I increase my accuracy avoiding overfitting? CNN-Keras-VGG16
As I asked in this question: Why are my predictions bad, if my accuracy in train is roughly 100% (Keras CNN) , my problem was Overfitting, so, I reduce the number of layers, and now I have this model:
vgg16_model = VGG16(weights="imagenet", includ... |
H: Why is pandas corr() deleting columns?
I'm doing a basic correlation analysis but for some reason pandas corr() is deleting columns, not sure why.
import pandas as pd
data = pd.read_csv("data.csv")
print(len(data.columns))
print(len(data.corr().columns))
Output:
100
64
AI: Pearson's correlation is the defau... |
H: What is a latent space vector?
I do not understand this about GANs.
Apparently the Generator is supposed to receive a latent space vector as its input. Yet I couldn't find an example of how I can implement it in Pytorch. This is a problem for me, because different posts suggest different approaches.
Is it simply an... |
H: use .apply() function to change values to a column of the dataframe
I have a dataframe which is the following:
and I would like to consider only the column of instructions and keep just the values push, test, mov, test ,....., so just the first word of each string inside each list. What I am doing is the following... |
H: Structure of LSTM gates
It is my impression that a single layer LSTM architecture consists of $t$ LSTM cells that are identical duplicates, where $t$ is the number of time steps. Then there are gates within the LSTM cell. I have struggled to find a rigorous explanation of what each “gate” actually consists of. Is e... |
H: Finding out which values lead Random tree to a decision
I have a dataset of machines that produce plastic parts. A camera evaluates whether a plastic part was produced correctly or not (binary classification). I'm trying to figure out which factors influence a part being wrongly produced. E.g. I have different temp... |
H: Get elements from lists in pandas dataframe
I have the following column of a data frame:
I get it by doing dataFrame['opcodes].
and I would like to consider only the first 20 and the last 20 elements of each list. Is there a way to do this?
I have tried to do the following:
dataFrame['opcodes_modified'] = dataFra... |
H: Replace entire columns in pandas dataframe
I would like to replace entire columns of a pandas dataframe with other columns, for example:
and I would like to replace the columns A and B. What I did is the following:
df['A']=dataFrame['opcodes'].values
df['B']=dataFrame['opt'].values
or also
df['A']=dataFrame['opco... |
H: How do I use multilevel regression models?
I have crime event data rows:
dayofweek1, region1, hour1, crimetype1
dayofweek2, region2, hour2, crimetype2 ...
and I want to use them as factors to model crime rates/probabilities at the region level.
I also want to use the resulting model to be able to input factor val... |
H: What is the reason behind having low results using the data augmentation technique in NLP?
I used Data augmentation technique on my dataset, to have more data to train. My data is text so the data augmentation technique is based on random insertion of words, random swaps and synonyms replacement.
The algorithm I us... |
H: Find Phone Numbers in messy data
I hope this isn't too basic of a question, I'm banking on the Data Science site description being true where it says "...and those interested in learning more about the field". I'm not looking for programming help, just validation that machine learning could help me with a problem.
... |
H: How do I force specified coefficients in a Linear Regression model to be positive?
Looking for a way to do this in Python. scipy.optimize.nnls forces all coefficients to be positive.
Some additional context: I have a data frame with a some explanatory variables and a response variable. When I run a regular linear r... |
H: Increase accuracy of classification problem
I am trying to build a classifier that predicts the compiler given some operations of assembly code. Here is the pandas dataframe:
What I do is using a TfidfVectorizer and select the features that have most predictive power by doing:
tfidf_vectorizer=TfidfVectorizer(max_... |
H: TypeError: 'GridSearchCV' object is not callable - how do I use a pickle of an SVM (Scikit-learn)?
I have created an SVM in Scikit-learn for classification. It works; it prints out either 1 or 0 depending on the class. I converted it to a pickle file and tried to use it, but I am receiving this error:
TypeError: 'G... |
H: Training a model sample by sample
I'm training a Scikit model but it seems that in all examples, they call the fit method on the entire training set. What I want to do however is call it per sample (i.e. looping through all samples). This has multiple reasons but most importantly are
MemoryError with my huge train... |
H: How reproducible should CNN models be?
I want to train several CNN architectures with Google Colab (GPU), Keras and Tensorflow.
Since the trained models are not reproducible due to GPU support, I would like to train the models several times and determine the mean and the standard deviation of the results.
I'm total... |
H: How to represent a dataset as a linked list-like graph?
I would like to visualize this data set using Python and probably a visualization tool like Matplotlib. The data set contains three columns: a user id with a question, a user id with an answer, and time. I would like to visualize this data set as a linked list... |
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