learn-python | 小白的Python入门教程：部分章节源码
kandi X-RAY | learn-python Summary
kandi X-RAY | learn-python Summary
learn-python
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Top functions reviewed by kandi - BETA
- Prints information about a message .
- Get an item from the list .
- Wrap wget .
- generate random number generator
- creates a new model
- Connect to the given socket .
- Remove an item from the dictionary .
- Saves the current mapping .
- Run n times .
- Generates a sequence of random numbers .
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Trending Discussions on learn-python
QUESTION
I'm working on a deep learning project and I tried following a tutorial to evaluate my model with Cross-Validation.
I was looking at this tutorial: https://machinelearningmastery.com/use-keras-deep-learning-models-scikit-learn-python/
I started by first splitting my dataset into features and labels:
...ANSWER
Answered 2021-Apr-06 at 06:08model = KerasClassifier(build_fn=create_model(), ...)
QUESTION
I'm following a tutorial on Naive Bayes at https://towardsdatascience.com/why-how-to-use-the-naive-bayes-algorithms-in-a-regulated-industry-with-sklearn-python-code-dbd8304ab2cf but I'm stuck on interpreting the reference in the third code block to two_obs_test[continuous_list]
The full code listing is ...
...ANSWER
Answered 2021-Feb-11 at 19:52The tutorial has too many gaps. I think a view of the insides of Naive Bayes without reading a whole book is better found at https://machinelearningmastery.com/naive-bayes-classifier-scratch-python/ . I am not persisting with the tutorial and I advise others to avoid it.
QUESTION
I have checked other questions covering the topic such as this, this, this, this and this as well as some great blog posts, blog1, blog2 and blog3 (kudos to respective author) but without success.
What I want to do is to transform rows whose values are under a certain threshold in X, but only those that correspond to some specific classes in the target y (y != 9). The threshold is calculated based on the other class (y == 9). However, I have problems understanding how to implement this properly.
As I want to do parameter tuning and cross-validation on this I will have to do the transformation using a pipeline. My custom transformer class looks like below. Note that I haven't included TransformerMixin as I believe I need to take into account for y in the fit_transform() function.
ANSWER
Answered 2020-May-27 at 13:08In the comments I was talking about this:
QUESTION
I have a binary classification problem where I need to predict the potential future trendy/popular products based on customer interactions during 2010-2015.
Currently, my dataset includes 1000 products and each product is labelled as 0 or 1 (i.e. binary classification). The label was decided based on customer interactions during 2016-2018.
I am calculating how centrality measures changed over time for each product during 2010-2015 as the features for my binary classification problem. For example, consider the below figure that shows how degree centrality changed over time for each product.
More specifically, I analyse the change of following centrality measures as the features for my binary classification problem.
- how
degree centralityof each good changed from 2010-2016 (see the above figure) - how
betweenness centralityof each good changed from 2010-2016 - how
closeness centralityof each good changed from 2010-2016 - how
eigenvector centralityof each good changed from 2010-2016
In a nutshell, my data looks as follows.
...ANSWER
Answered 2019-Aug-31 at 05:11There are many types of cross validation similar to how there are many types of neural networks. In your case you are trying to use kfold cross validation.
In the question you linked, it correctly states that kfold cross validation should not be used with time series data. You can’t accurately evaluate your model if you are training on data and then testing on data that occurred before the training data.
However, other forms of cross validation (such as the mentioned sliding window or expanding window) will still work with your time series data. There is a function in sklearn that splits the data using the expanding window method. https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html
With all that said, I am not sure if you are really using time series data. If you simply have the centrality scores for each year as a separate feature, then the order of your data does not matter since each item is only one data point (assuming that the scores of one item don’t impact another). In that case you can use kfold cross validation and other networks that work with iid data. You could even use non neural networks such as SVMs or decision trees.
QUESTION
I am currently trying to grasp the exact name of argv function (if it can be called a function) that can be imported from sys or system-specific parameters. I found 3 definitions:
So which one is it? Perhaps it doesn't matter how one calls it? Does it even have an accepted name?
Thanks everyone!
...ANSWER
Answered 2017-Oct-18 at 12:45It doesn't really matter. It's a list (not a function), and the name argv is just borrowed from the conventional name used in C. Most of the time, you are better off using a library like argparse to process the command line arguments, in which case you won't even be using sys.argv directly.
QUESTION
I'm testing a text-based game I've been making to learn Python. The last few days I have been busy finding a solution for a problem I keep encountering. I have tried multiple test methods, but they all end up giving me the same error.
The problem is the following AssertionError (using py.test):
ANSWER
Answered 2017-Jul-25 at 15:28You need to be able to identify each instance:
QUESTION
I am following step 3 of this example:
...ANSWER
Answered 2017-Jan-06 at 19:25fit(x,y) is a method that can be used on an estimator.
In order to be able to use this method on model you would have to create model first and make sure its of an estimator class.
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