Words are easy, like the wind;
Faithful friends are hard to find.
The uncountries are places that don't exist, but perhaps should. If you're starting your own country or are hoping to secede from your current employer (here's looking at you States of the US), you might find this list useful.
The list of uncountries is generated by training on list of 257 countries and territories.
Here's my bucket list of where I'm going next:
Below are the alphabetically first 4–10 letter single-word uncountries for each letter. In some cases, no names of a given length were generated for a given letter.
And below are uncountries that are composed of compound words. The neural network doesn't always do a good job in capitalization.
Here are all some lists with common suffixes
*nia Ariania Aruenia Bamenia Bolsnia Bukania Caminia Carenia Copania Eniania Eruinia Eryinia Eyuinia Fvounia Gapania Gorania Guyinia Imgania Lebania Lepania Mezania Pagonia Pamonia Piainia Pirania Saminia Sesinia Simania Somenia Sorinia Tinonia Turunia Urzenia Badetcinia Damalhania Denwarinia Inteniania Mangevinia Seregiania Tezadtinia Tudennenia Akinia Arenia Arunia Bocnia Boinia Bounia Buinia Burnia Byunia Caunia Eminia Gainia Geenia Geinia Giania Guania Guinia Guonia Gwinia Jhunia Jiinia Jirnia Kcenia Leinia Lornia Neenia Rernia Ruenia Sannia Shinia Siinia Siunia Suinia Uninia Vasnia Arefeonia Bevomania Dacucania Eziboonia Gibstania Klbininia Setrounia Shlatania Suunienia Teroninia EwDirireonia Aeirania Bemginia Bunyonia Canmania Carginia Carnania Cosrania Culiinia Cumiinia Duinania Ezupinia Geziania Guinenia Guurania Konvonia Lalzinia Lertania Marbania Nandania Narnania Nenconia Pastania Sadiania Sazcinia Sigwenia Smeminia Sonconia Surbania Taigonia Tebcania Tendania Unyrania Cania Conia Fania Henia Jania Jonia Kinia Lonia Mania Ninia Nonia Sania Tenia Tonia Vania
*lan Anualan Binelan Biselan Comelan Donolan Eduulan Iferlan Ilaslan Iudelan Papilan Potalan Srinlan Takilan Tamglan Cemuneilan Gehsyanlan Mecineslan Amurenoilan Aralan Cralan Geilan Inilan Innlan Kerlan Nanlan Sorlan Tnulan Beugeilan Condamlan Cunogslan Gantiulan Geevallan Gienyslan Memsinlan Mertorlan Minnaulan Mururolan Neminolan Sandeslan Sennerlan Titorilan Vertonlan Andenlan Betarlan Ceneslan Cunmelan Curislan Femanlan Geamilan Keberlan Larielan Meloelan Menrulan Molielan Otenelan Redallan SDatelan Selenlan Alan Glan Tlan Bolan Bulan Culan Galan Malan Selan Solan
*land Garland Hasland Ujoland Bandesland Benhelland Bhqlalland Dhinioland Lenkalland Macgalland Vuleslland Caland Feland Maland Saland Anderland Cemerland Geunoland Lutkaland Mowurland Panciland Parraland Anreland Asealand Hzuuland Maerland Masrland Memoland Namaland Navaland Ponoland Tuysland Vetaland
*ana Amynana Balpana Burgana Congana Fuubana Gainana Gaulana Guiiana Somuana Tartana Vehcana Cunheqrana Berniwhpana Antana Argana Buvana Mabana Merana Mobana Relana Rucana Semana Sikana Nteradana Gitanana Hana Lana Mana Sana Giana Guana Gvana Toana
*ica Cinuica Deyrica Goitica Maltica Mannica Merlica Peotica Raryica Sortica Stamica Sumhica Tektica Tiumica Utiuica Bemgbicica Aniica Bapica Narica Sanica Selica Sibica Gatuitica Iuperiica Ventalica Buuntica Bwentica Sorgeica Uica Baica Umica
*can Banecan Celican Jelican Pelecan Deslisacan Hatendacan Leucan Noccan Tircan Tlycan Shaylican Suniracan Cerarcan Emunecan Gepuucan Mamescan Salgican Vongican Ucan
*dan Euvadan Gtardan Monmdan Seundan Srisdan Unendan Banitisdan Ringkeldan Bildan Landan Saldan Soldan Sordan Tamdan Gakgasdan Mremaldan Stelosdan Lapardan Siwesdan Srunadan
*stan Baystan Caistan Velstan Gentiastan Getnicistan Naporrestan Gistan Mastan Tengastan Sinistan
*tar Lalatar Sanktar Simntar Somytar Swettar Temitar Burekertar Jartar Tantar Unitar Gornitar Satar
To achieve a `k` index for a movement you must perform `k` unbroken reps at `k`% 1RM.
The expected value for the `k` index is probably somewhere in the range of `k = 26` to `k=35`, with higher values progressively more difficult to achieve.
In my `k` index introduction article I provide detailed explanation, rep scheme table and WOD example.
The effect is intriguing and facetious—yes, those are real words.
But these are not: necronology, abobionalism, gabdologist, and nonerify.
These places only exist in the mind: Conchar and Pobacia, Hzuuland, New Kain, Rabibus and Megee Islands, Sentip and Sitina, Sinistan and Urzenia.
And these are the imaginary afflictions of the imagination: ictophobia, myconomascophobia, and talmatomania.
And these, of the body: ophalosis, icabulosis, mediatopathy and bellotalgia.
Want to name your baby? Or someone else's baby? Try Ginavietta Xilly Anganelel or Ferandulde Hommanloco Kictortick.
When taking new therapeutics, never mix salivac and labromine. And don't forget that abadarone is best taken on an empty stomach.
And nothing increases the chance of getting that grant funded than proposing the study of a new –ome! We really need someone to looking into the femome and manome.
An exploration of things that are missing in the human genome. The nullomers.
Julia Herold, Stefan Kurtz and Robert Giegerich. Efficient computation of absent words in genomic sequences. BMC Bioinformatics (2008) 9:167
We've already seen how data can be grouped into classes in our series on classifiers. In this column, we look at how data can be grouped by similarity in an unsupervised way.
We look at two common clustering approaches: `k`-means and hierarchical clustering. All clustering methods share the same approach: they first calculate similarity and then use it to group objects into clusters. The details of the methods, and outputs, vary widely.
Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. Nature Methods 14:545–546.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Logistic regression. Nature Methods 13:541-542.
Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Classifier evaluation. Nature Methods 13:603-604.
In this redesign of a pie chart figure from a Nature Medicine article , I look at how to organize and present a large number of categories.
I first discuss some of the benefits of a pie chart—there are few and specific—and its shortcomings—there are few but fundamental.
I then walk through the redesign process by showing how the tumor categories can be shown more clearly if they are first aggregated into a small number groups.
(bottom left) Figure 2b from Zehir et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. (2017) Nature Medicine doi:10.1038/nm.4333
After 30 columns, this is our first one without a single figure. Sometimes a table is all you need.
In this column, we discuss nominal categorical data, in which data points are assigned to categories in which there is no implied order. We introduce one-way and two-way tables and the `\chi^2` and Fisher's exact tests.
Altman, N. & Krzywinski, M. (2017) Points of Significance: Tabular data. Nature Methods 14:329–330.