#multinominal

[isobug]

Alt. Abronominal /Namefluid / Nomifluid flags

This is based off of this Namefluid flag, but edited to be more similar to other Abro- flags color-wise since I use that term over Namefluid / Nomifluid (though you're welcome to use it if you prefer those terms!) and also for sight disability reasons

The first flag has a plain white second stripe and the second has a slight tint on it to make it less bright those who find that format more accessible!

Help with ALT text is appreciated, free to use for anyone as always!

[hypnosiacon-archived]

Genderfluid, Pronounfluid, Nomifluid, Kinfluid, Xenogender, Voidpunk, Polykin, Multinominal Combo Flag

✖ Requested by Anon

[jaydenchip404]

I physically cringe when I see my name

So lately, I've started to cringe when I see or hear my birth name. I really don't like it. I don't know why, but I do. I guess because it's too gurly for my taste. but I don't know. I just want to legally change my name to 'Jayden'. It's gender-neutral, and I like it much more, but Jayden still isn't perfect enough for me to feel comfortable.

For Christmas my mom bought me a sign with my deadname on it and I nearly had a mental breakdown /j

I hate that sign so much, and it sits on my vanity under some pillows.

I tried to hint at her that I hate my deadname, like saying that no one knows how to pronounce my dead name (since it's true). She heard my doctor say my name wrong. I literally told her I liked the name Jayden. But she still hasn't caught on, somehow.

[jinxy]

found a good album and we share a name. retconning it into my backstory

[antiheroismm]

First coined terms, Sharequeermate and the terms under its umbrella!

Sharequeermate: A term that two or more people can use when they share their genders, pronouns, and/or names, like soulmates!

Flag:

Gendermate: A term that can be used by two or more people when they share each other's genders from their identity, collection/hoard, ect., whether it be mutually or by certain sides. This term can be used by anyone, but it could fit well with:

People are multigender/polygender.

People who are gendercollectors/genderhoarders.

People who are genderfluid, gendetflux and/or fluidflux.

This can also apply to system alters/headmates.

Flag:

Nomimate: A term that can be used by two or more people when they share each other's names from their identity, collection/hoard, ect., whether it be mutually or by certain sides. This term can be used by anyone, but it could fit well with:

People are multinominal.

People who are namecollectors/namehoarders.

People who are nomifluid, nomiflux, etc.

This can also apply to system alters/headmates.

Flag:

Pronomate: A term that can be used by two or more people when they share each other's pronouns from their identity, collection/hoard, ect., whether it be mutually or by certain sides. This term can be used by anyone, but it could fit well with:

People are multipronominal.

People who are pronouncollectors/pronounhoarders.

People who are pronounfluid, pronounflux, etc.

This can also apply to system alters/headmates.

Flag:

I will soon provide IDs and meanings for the colors, so please stay tuned!

Coined by me! Credit if reposted.

[mariana-creature]

Intro post time plus testing out the keep reading feature

I am Mykonos, a dragonkin. This is just my sideblog for dragon stuff I guess, if you want the main it's in my blog description and I'll tag it here: @xiathiau-myshif

Go over there for a full intro post plus DNI. Some info: I am multinominal, so I use different names for each kintype, and I may start signing my posts with them.

I am also using this post to get a written description of myself down. Profile picture is 'Sea Serpent' by Yuki Sato. I will change it if I find a dragon picrew because I can't draw for shit.

Here's what I know about what I look like:

I am very large (not sure exactly how large, but something like 3000-4000 feet?). I'm dark blue with lighter spots around my body, mostly concentrated on my back. I have a pair of short, white ivory horns jutting out from the back of my head. My eyes are bright teal with slit pupils and I have one pair of wings, the same colour as my body.

All along my body I have bioluminescent patches, mostly circular or elliptical. My eyes also glow in the dark. My talons on both front and back are webbed. Down my back I have spines coming off my scales, connected with a thin, translucent membrane. It is similar to my tail, which is an arch-shape of scaled with the same membrane.

I have very sharp teeth. My roar is high and sounds a little like a whistle mixed with a scream.

If I forgot anything I'll add it when I remember

[polyg-lotte]

day 9 of 30 of productivity

attended my classes which were really interesting! we discussed some statistical methods we're probably using for this period. i hadnt known how to do multinominal regression before but it sounds cool. took a long walk with a friend through the woods which was GORGEOUS, and read a paper in preparation for my bachelor thesis! did swedish on duolingo, and ill do my anki for the day before bed. sleep time !

[techblog-365]

NAIVE BAYES ALGORITHM

In a world where many manual operations are mechanized, the definition of the word ‘manual’ is evolving. Computers can play chess, perform surgery, and develop into smarter, more humanlike machines with the aid of machine learning algorithms.

What is Naive Bayes Algorithm?

The machine learning algorithm is divided into categories, in which Naive Bayes Algorithm falls under the umbrella of supervised machine learning algorithm. It is a classification method built on the Bayes Theorem and predicated on the idea of predictor independence. A Naive Bayes classifier believes that the presence of one feature in a class has nothing to do with the presence of any other feature. For example

The Bayes model is simple to construct and especially helpful for very big data sets. Along with being straightforward, Naive Bayes is known to perform better than even the most complex classification techniques.

It provides a way of calculating the posterior probability by the given equation below:      

                       Where P(c|x) = posterior probability of class (c) given predictor (x).

                                    P(x|c) = Prior probability of predictor.

Types of Naive Bayes Algorithm

Three different Naive Bayes model types may be found in the Scikit-Learn library which are as follows: -

Multinominal Naive Bayes

Feature vectors represent the frequencies with which certain events have been generated by a multinomial distribution. This is the event model that is typically used for document classification.

Bernoulli naive bayes:

In the multivariate Bernoulli event model, features are independent Booleans (binary variables) describing inputs. Like the multinomial model, this model is popular used for document classification tasks, where binary term occurrence (i.e., a word occurs in a document or not) features are used rather than term frequencies (i.e., frequency of a word in the document).

Gaussian Naive Bayes:

 We assume that the values of the predictors are samples from a gaussian distribution when they take up a continuous value and are not discrete.

Below code can be implemented of Gaussian Naive Bayes classifier using scikit-learn.

# load the iris dataset

from sklearn.datasets import load_iris

iris = load_iris()

# store the feature matrix (X) and response vector (y)

X = iris.data

y = iris.target

# splitting X and y into training and testing sets

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=1)

# training the model on training set

from sklearn.naive_bayes import GaussianNB

gnb = GaussianNB()

gnb.fit(X_train, y_train)

# making predictions on the testing set

y_pred = gnb.predict(X_test)

# comparing actual response values (y_test) with predicted response values (y_pred)

from sklearn import metrics

print("Gaussian Naive Bayes model accuracy(in %):", metrics.accuracy_score(y_test, y_pred)*100)

Output:

Gaussian Naive Bayes model accuracy (in %): 95.0

Applications of Naive Bayes Algorithm/Classifier

Real-time Prediction: Naive Bayes is a quick classifier that is eager to learn. As a result, it might be applied to real-time prediction.

Multi-class Prediction: This algorithm is very widely renowned for its ability to predict many classes. Here, we can forecast the likelihood of several target variable classes.

Sentiment analysis, spam filtering, and text classification: Because they perform better in multi-class situations and follow the independence criterion, naive Bayes classifiers are frequently employed in text classification and have a greater success rate than other methods. It is therefore frequently used in Sentiment Analysis and Spam Filtering (to identify spam e-mail) (in social media analysis, to identify positive and negative customer sentiments)

Recommendation system:  Naive Bayes Classifier and Collaborative Filtering work together to create a system that filters opportunistic information and forecasts whether a user will find a specific resource appealing or not.

Advantages of Naive Bayes Algorithm

A Naive Bayes classifier outperforms other models when the independent predictor assumption is valid.

To estimate the test data, Naive Bayes just needs a modest amount of training data. So, there is a shorter training period.

It's simple to use Naive Bayes.

Disadvantages of Naive Bayes Algorithm

The main premise of Naive Bayes is that independent predictors exist. All of the attributes are implicitly assumed to be independent of one another by Naive Bayes. We rarely find a set of predictors that are entirely independent in the real world.

If a categorical variable in the test data set has a category that wasn't included in the training data set, the model will give it a probability of 0 (zero), and it won't be able to predict anything. This is commonly referred to as Zero Frequency. We can utilize the smoothing method to resolve this. Laplace estimate is one of the simplest smoothing methods.

About Rang Technologies: Headquartered in New Jersey, Rang Technologies has dedicated over a decade delivering innovative solutions and best talent to help businesses get the most out of the latest technologies in their digital transformation journey. Read More...

[hypnosiacon-archived]

what's in your inbox?

(Im Sorry for annoying you but notion still don't work for me and just do endless loading qwq)

Good thing for you, I don't write my requests in my to-do ksjdnks

Aaanyway, inbox check...

Saphilunamore Objectum / Objectix

TMA Pronouns and names

Combo flag: genderfluid, pronounfluid, nomifluid, kinfluid, xenogender, voidpunk, polykin, multinominal

Platoniflux matching my erosflux flag

Nominalgender alt

Almutorenic alt

Doors object xenogender

Zombiecore xenogender flag

Domestic + Xenial attraction combo

Constel for multiple foxes

Constel for multiple wolves

Constel for multiple bears

Archivist omninoun

Coral Reef hearthic

Mr Kat from Kid vs Kat otherkin / fictionkin flags

Bonus what are not reqs, I swear I am going to clean all my inboxes....

Vid from mr-amazing-spy

Vid from gender-mailman

Attack from 🌊🐺 anon

🌊🐺 Something something I forgor

Ask game x2

List of purple and violet shades for my purple pronoun list

Images from gender-mailman

[jackolanternpump-kin]

I know there are at least a small group of other people out there that have lots of names or consider themselves name collectors/name hoarders, but I’m wondering if anybody else slowly has their preferred name change over time like me.

My favorite name for myself has been Jack for some years, then it was Ghost for about a year, and now I’m thinking I’m liking Wil the best. (Yes, those last two are related to the Dream SMP characters. The first one isn’t.) Typing this out, I’m realizing how my “main names” have always referred to my identity or interests.

I’ve only asked people to change names twice though, and that was before I was a name collector. I don’t want to bother people. Don’t even get me started on getting people to call you multiple names at once; I’d never try asking.

I suppose Jack is as good of a name as any. But what if I just... changed my screen name to Wil with no comment. Maybe I’ll just put Wil first before the other names, since I still like all my other names as well.

Me: Communication is key! Also me: *doesn’t communicate*

I really wish I could just think of and be satisfied with one name for my whole life. I want to change my legal name one day, so hopefully I’ll figure all of this out soon.

[themogaidragon]

Multifour

Multifour is a term that refers to someone who is multigender, multisexual and/or m-spec in general, multipronominal, and multinominal. One's name, pronouns, gender, and orientation be fluid or static, situational or non-situational, etc. As long as one's labels and identity fall under the umbrella of all of these terms, they may use it.

Similar terms include Fluid-fluid-fluid, a combination term for name/pronoun/and genderfluid individuals.

"Multifour" was coined by fandom user johnnienotjohnny on June 19, 2021.

[yourlocalquoi]

One of my names is Indy

Which is kinda sorta short for Indiana Jones /hj

[trutranstrender]

Multinominal Flag!

I really hope this flag isn’t similar to anything!

So this is the flag for being multinominal like me, so having more than one name!

The blue represents masc names, pink represents fem names, purple represents unisex names, and the yellow represents completely neutral names! It’s all pastel because i just like pastels -u-

And here’s the less pastel-ey one for those who dislike pastel colours! Colours represent the same things, this one just has a different design that kind of looks like the old bi flag but with circles! 

[beyond-mogai-pride-flags]

Namefluid Pride Flag

Namefluidity: when your name changes; having fluctuating name(s).

This could be also known as abronominal. Similar to multinominal (having multiple names for yourself, polynominal/plurinominal).

[Image: five stripes colored with pale violet, white, light cyan, greyed black and brown]

-Ap

[yassrael-hands]

ed babygirl you are so peter nureyev coded

[neopronouns]

Hi dexter, this isn't a request but just a general question I've been having for a while but I don't really have anyone to turn because they don't know either. Is it okay to have a sort of "list" with names that one is comfortable with being called? Liek a pronoun list but for names? I'm genderfluid so my relationship to certain name changes. If you don't want to reply that's fine, thank you for reading it and I hope you have a great day!

absolutely!! i've known and seen many people who use lots of names, either all at once or changing with their gender. also, if you want a term for your experience, you might like multinominal or namehoarder/namecollector!