samm | SAMM stands for Software Assurance Maturity Model | Cybersecurity library
kandi X-RAY | samm Summary
kandi X-RAY | samm Summary
SAMM (Software Assurance Maturity Model ).
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of samm
samm Key Features
samm Examples and Code Snippets
Community Discussions
Trending Discussions on samm
QUESTION
Can I use AdaBoost with random forest as a base classifier? I searched on the internet and I didn't find anyone who does it.
Like in the following code; I try to run it but it takes a lot of time:
...ANSWER
Answered 2021-Apr-07 at 11:30No wonder you have not actually seen anyone doing it - it is an absurd and bad idea.
You are trying to build an ensemble (Adaboost) which in itself consists of ensemble base classifiers (RFs) - essentially an "ensemble-squared"; so, no wonder about the high computation time.
But even if it was practical, there are good theoretical reasons not to do it; quoting from my own answer in Execution time of AdaBoost with SVM base classifier:
Adaboost (and similar ensemble methods) were conceived using decision trees as base classifiers (more specifically, decision stumps, i.e. DTs with a depth of only 1); there is good reason why still today, if you don't specify explicitly the
base_classifier
argument, it assumes a value ofDecisionTreeClassifier(max_depth=1)
. DTs are suitable for such ensembling because they are essentially unstable classifiers, which is not the case with SVMs, hence the latter are not expected to offer much when used as base classifiers.On top of this, SVMs are computationally much more expensive than decision trees (let alone decision stumps), which is the reason for the long processing times you have observed.
The argument holds for RFs, too - they are not unstable classifiers, hence there is not any reason to actually expect performance improvements when using them as base classifiers for boosting algorithms, like Adaboost.
QUESTION
I use a Room database class on Android Studio.
I have the following entities:
User, Address, Geo, Company, Album, Photo, AlbumPhotoCrossRef (there's many-to-many relationship between Album and Photo). And I added Word too just to test.
The code for these entities are added below.
When I use only Word (comment out other classes in the entities =
part, it works, I can see the table via DatabaseInspector.
But when include all entities, the database don't even open, I can't even see name of the database on DatabaseInspector.
And I get the following error:
...ANSWER
Answered 2021-Apr-11 at 10:42You've changed the schema (structure) without changing the version number. Room's integrity checking has detected the change and hence the exception.
As you have MIGRATION_1_2 you probably just need to change the version number from 1 to 2 as per :-
QUESTION
I am currently using daily financial data to fit my SVM and AdaBoost. To check my result, I tried AdaBoost with n_estimators=1 so that it would return same result as I just run a single SVM.
...ANSWER
Answered 2021-Mar-17 at 07:59You haven't done anything wrong. The classifier sets a new random state every time you run it. To fix that just set the random_state
parameter to any value you like.
Eg:
QUESTION
npm does not support Node.js v15.5.0 as well as v14.15.3
npm Version: 5.6.0
I upgraded it trough the command: npm i -g npm-upgrade
But I don't get version 6, I always get version 5.6.0
I also tried different Node.js versions according to 426750.
I tried following Node.js versions: v15, v14, v12, v9. It doesn't matter which Node.js version I install, i always get the samme error.
I also removed Node.js and updated it as recommended in 47226238, 63196042.
I have no Idea how I can fix this problem. Do you have any suggestion?
...ANSWER
Answered 2021-Jan-18 at 14:53The correct command to update npm
is npm install -g npm
. At the time of this writing, that will install npm@6.14.10. (If it doesn't, try npm install -g npm@6
.)
Installing npm-upgrade
instead will install a CLI that updates package.json in projects. It will not update npm
itself.
EDIT: The version compatibility stuff is just a warning. Based on the comment below, the ERR! cb.apply is not a function
stuff is the real problem. You may have multiple versions of npm
or node
installed in different paths and your PATH
or alias configuration is causing incompatible versions to run with each other.
EDIT (continued): If you are using nvm
as a version manager, you can downgrade to a previous version, remove/reinstall the current version of Node.js, and you will have a compatible version of npm
. If you are not using nvm
, installing it (assuming you are on a development machine and not experiencing these issues in production) and using node
and npm
provided by it should also solve the issue.
EDIT PART 3: I just noticed you are running Node.js 15.5.0. That ships with npm@7
so do npm install -g npm@7
. If that doesn't work, find your executable paths for node
and npm
. (On UNIX-like operating systems: command -v node
and command -v npm
.) If they are not in the same directories, that sounds like a problem and you should investigate. It will probably be easiest/best to use the npm
that is in the same directory as node
. You can try that out by using the full path. If that works, figure out what's wrong with your PATH
or your aliases that you're using a different npm
and fix that.
QUESTION
I have a Keras model and want to boost it using sklearn's AdaBootClassifier. Unfortunately I get the following error message and have no idea how to solve it. I would be very happy about any help!
ValueError Traceback (most recent call last) in () ----> 1 boosted_classifier.fit(X,y)
3 frames /usr/local/lib/python3.6/dist-packages/sklearn/ensemble/_weight_boosting.py in _boost_discrete(self, iboost, X, y, sample_weight, random_state) 602 # Only boost positive weights 603 sample_weight *= np.exp(estimator_weight * incorrect * --> 604 (sample_weight > 0)) 605 606 return sample_weight, estimator_weight, estimator_error
ValueError: non-broadcastable output operand with shape (670,) doesn't match the broadcast shape (670,670)
This is my code:
...ANSWER
Answered 2020-Oct-28 at 15:47I found an easy solution for myself. I just added the following prediction function to my MyKerasClassifier Class and it works :)
QUESTION
I have a Dictionary>
that needs to be sorted depending on a certain value of the child dictionary.
e.g
...ANSWER
Answered 2020-Oct-02 at 09:18This is easy, and you probably don't even need to know the type as it'll work it out for you:
QUESTION
I have problem with remove tag by class its my script:
...ANSWER
Answered 2020-Jun-09 at 07:19Its actually remove span from your soup but you are not changing your str
value but printing old one.so you didnt recognize it. If you want to change your str
after some operation just change description_filter(str)
to
QUESTION
I want to center my webpage, and center the content on my web page, but the justify content (in css) does not seem to work. I have tried setting max-width in both precentage and pixels, and added and removed margins. I would really apreciate all help!
i have multiple div elements inside other elements, including a menu, which i would like to center, and even distrubetly the text inside the menu. Then i have an header which have a fixed size due to poor resolution. The only way i have managed to center anything is by setting margin to auto, but i believe that overwrites the flexbox system? I also tried creating a new div wich incapsulates everything (Innpakning1), but that only gave me two divs wich did not do what i hoped for.
...ANSWER
Answered 2020-May-10 at 07:20in flex-direction: column
you should set align-items: center
for everything be centerilize,add justify-content: center
to body
and align-items: center
to div with class .innpakning
QUESTION
The values of the value attribute corresponding to the decision tree classifier stubs being used with an AdaBoostClassifier are not matching expectations and I can not determine what the values are indicating. I would like to understand the values to aid in analyzing the behavior of the stub estimator and the contribution the stubs are making to the AdaBoostClassifier. Similar questions to Stackoverflow don't correlate with my data.
Version information
- python: 3.6.5
- sklearn version: 0.20.2
The DecisionTreeClassifier stubs are configured as:
...ANSWER
Answered 2019-Jan-11 at 00:03I tried reproducing it on a generated dataset:
QUESTION
I am trying to add a link to a product if it has a certain attribute value. This is what I have
...ANSWER
Answered 2020-Apr-09 at 17:55You can use slug and title property that came from $term object. Try like this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install samm
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page