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[Powered by Google Translate] Youve 'forsit auditus populus loqui de jejunare vel efficiens algorithm

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ad capiendum peculiaris vestrae negotium,

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sed quid exacte sibi uult, pro an algorithm esse jejunare vel efficiens?

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Atqui vera fringilla aliquam nunc non loquitur,

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quasi secunda vel minutes.

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Hoc est, quia computatrum hardware

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et software variant ASPERITER.

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Conventiculo currere posset tardior quam tua,

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quoniam Im 'cursor eam super antenatum computer,

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aut quia ego contigerit lascivio an online video venatus

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simul quod hogging omnibus memoria

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aut possem esse currens conventiculo diversas per software

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aliud, quo machina parvo elit.

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Est ac comparantes poma et oranges.

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Just quia meum tardior computatrum sumit amplius

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responsum reddere, quam tuus

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non dicit habetis magis efficens algorithm.

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>> Sic, cum nos non possit directe comparare runtimes de progressio

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in minutis secundis aut minutes,

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quomodo nos comparare II diversis algorithms

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cuiuscumque sint hardware vel software environment?

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Creo a plus uno modo mensuras algorithmic efficientiam,

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computatrum scientists et mathematici cogitaverunt

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conceptibus mensurae asymptoticus multiplicitate protracta et

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et adnotatio vocatur 'Big Ohnotation'

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pro describens hoc.

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Quod pertinet ad rationem, f (x)

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cuius iussu G (x)

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si esse aliquod (x) pendo, x ₀ et

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constanti C, quod

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f (x) sit minor vel equalis

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assiduum illud temporibus g (x)

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pro omnibus x maior quam x ₀.

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>> Rationem, sed ne metuit a.

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Quid hoc actu autem dico in minus speculatiuis terminos?

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Bene, suus 'basically viam analyzing

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velocitate protracta et scriptor runtime crescit asymptotically.

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Hoc est, ut moli vestra inputs auget ad infinitum,

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dicunt, vestri 'voluptua intellegeretur compluras molis M comparari ad array molis X.

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Quomodo runtime of vestri progressio crescat?

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Pro exemplo, imaginari computatis numerus characterum

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in filo simplicissima via

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 per ambulationem per totum chorda

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littera-by-littera et addendo I ad calculus pro singulis character.

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Hoc algorithm dicitur run in linearibus tempus

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secundum numerum personarum,

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'N' in nervo.

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Denique subit O (n).

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Quid est hoc?

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Bene per hunc modum tempus

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percurrere totius chordae

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numerum proportionalem esse viris.

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Supputatis numerum characters in a XX-character chorda

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ut saltem duplo longius itur

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numerare characters in X-character nervo,

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quia omnes characteres respicias

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Et idem fiat cuique temporis respicere.

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Cum te augere numerum personarum,

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in runtime augebit linearly cum input longitudine.

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>> Nunc, finge si statueris linearibus tempore,

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O (n) sicut non hercle vobis?

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Maybe vos erant 'thesaurizantes ingens chordarum,

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extra tempus et futurum non possunt

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percurrere omnes eorum characters computatis unus-per-unum.

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Sic aliud placet temptare.

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Quis si vos accideret iam reponunt numerum characters

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in nervo, inquiunt, in variabilis vocatur 'Len,'

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mane die in progressio,

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ante etiam vos repono ipsa prima character in vestri chorda?

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Ergo omnia scire putes facere, filum longum,

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est reprehendo quem valorem variabilis illius est.

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Ne respicias se corda omnium,

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et accessu ad valentiam variabilis quasi Len consideratur

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an asymptotically tempus constans operationem,

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aut O (I).

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Quid est hoc? Bene, memorare quid asymptotici complexitate significet.

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Quomodo habet runtime alteratio secundum moli

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tui inputs crescit?

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>> Nisi forte in maiore esset personarum numerus nervo conetur.

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Bene facitis quod non refert quam magnus nervo

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etiam a million characters longa,

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omnes youd 'have efficio invenire chorda est scriptor mensuram aditus,

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est perlegere valor variabilis Len,

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quas tu iam fecit.

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Input in longitudine, quae est longitudo fili quaerens es,

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fugit te ratio non convenit omni velocitate.

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Haec pars vestri progressio cursurus esset aeque ieiunium in a unus-character chorda

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et mille-character nervo,

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Et ideo iam hoc esse propositum ut ad tempus cursus semper

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input secundum magnitudinem.

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>> Nimirum, illic 'a Incommodum.

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Consumaveris susicivus memoria tractus in vestri computer

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thesaurizantes variabilis

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et susicivus tempus necessarium vos

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ut faciam actualis repono de variabilis,

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sed ipsum punctum stat adhuc,

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excogitato usquequo vestra chorda erat

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non omnino pendet longitudo fili.

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Ita decurrunt O (I) vel semper nunc.

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Non utique diceretur

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ut vestri codice currit I gradum,

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Sed quamvis multa passus est,

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inputs nisi quantitas variabilis,

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suus 'etiam asymptotically constans quae nos repraesentat ut O (I).

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>> Sicut vos probabiliter potest augurari,

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ibi multi et diversi sunt magnus O runtimes ut metiretur algorithms cum.

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O (n) ² algorithms sunt asymptotically tardior quam O (n) algorithms.

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Id est, secundum particularum numerum (n) oritur,

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eventually O (n) ² algorithms assumam plus temporis

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quam O (n) algorithms ad currendam.

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Hoc non significat O (n) algorithms semper currere velocius

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quam O (n) ² algorithms, etiam in eadem environment,

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in eadem accumsan, odio.

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Maybe enim parvae input magnitudines,

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 O (n) ² algorithm ut etiam operemur velocius,

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sed, eventually, sicut input mole auget

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ad infinitatem, O (n) ² algorithm scriptor runtime

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mos eventually eclipsare runtime gentis O (n) algorithm.

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Iustus amo ullus quadraticum mathematica functio

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 mos eventually comprehendam ulla linearibus functio,

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quamvis ratione lineae incipit cum initio capitis.

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Magnum opus si tibi data

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algorithms ut run in O (n) ² tempus potest realiter terminus sursum tarditatem vestri progressio,

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sed enim parvae input magnitudines,

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attende ne forte tu.

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>> Alius asymptotici complexitate est,

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logarithmica tempore, O (log n).

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Haec celeriter currit exemplatum algorithm

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est classic binariae search algorithm,

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pro inveniendis elementum jam in-sorted list elementorum.

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>> Si vos non sciunt quid binariae search facit,

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Ego puteus 'persolvo eam vobis realiter cito.

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Dico vobis quaeritis Sit numerus III

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in hoc aciem: integri.

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Media acies videt elementum

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rogans, "volo elementum maior aut aequalis, aut minor?"

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Si par, sic magnus. Invenisti elementum et facta es.

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Si est maior, elementum scitis

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in ordine ad dexteram,

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Eodem modo et in futuro expectamus,

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Et si minus est, quia tunc est in sinistram.

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Is processus tunc iterari cum minori-amplitudo array

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donec rectam elementum inventus est.

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>> Iste potens algorithm secet, in aciem mole in dimidia cum singulis operationem.

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Sic, reperire elementum in sorted array molis VIII,

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ad summum (stipes ₂ VIII),

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aut III harum operationum,

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tardata medium elementum, tunc secans array in dimidia erit requiritur,

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Cumque hac array molis XVI sumit (stipes ₂ XVI),

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aut IV operationes.

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Ut 'tantum I plus operatio per duplices-amplitudo ordinata.

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Duplicando moli, in aciem

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auget runtime per solum I FRUSTUM huius code.

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Iterum, tardata medium elementum album, tunc rumpendi.

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Sic tempus dictum operari logarithmica,

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O (log n).

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Sed expecta, dicitis,

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unde hoc non attenditur per ordinem elementum sit quaeritis?

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Si forte prima pars dextra spectas?

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Igitur et tunc solum sumit I operationem,

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neuer grandes facit album est.

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>> Bene, ut 'quare computatrum scientists habere plures termini

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pro asymptotici complexitate quae reverberant optimus-casu

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et pessimum-casu theatrica an algorithm.

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Magis proprie finis superioris et inferioris

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in runtime.

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In optimo casum pro binariae search, nostra elementum est

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vox illic in medio,

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quod vos adepto eam in tempus constans,

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cetera utcumque ordinatus est magna.

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Symbolum solebat hoc enim est Ω.

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Et hoc dicitur currere algorithm Ω (I).

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Optime tamen habet quiddam brevi

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neuer magnus, in aciem est,

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sed in pessimum casu,

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habet ad faciéndam (log n) split compescit

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ut in ordine ad res.

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Pessimum-casu superiorem terminos referuntur ad cum magnus "O" ut vos iam familiari.

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Sic, suus 'O (log n), sed Ω (I).

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>> A linearibus search, per oppositum

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quod omnia quae in apparatu perambula

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Unum invenire vis,

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est ad optimus Ω (I).

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Prima iterum pars vis.

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Unde non refert quantum ad bellum.

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Maxime in re illud in novissimo agmine elementum.

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Ergo per te ire in aciem n elementa inveniuntur,

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sicut si quaeratur III.

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Ita fuerit, currit in O (n) tempus

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quod est in ratione numeri particularum in ordine.

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>> Unus plus symbolum adhibitus est Θ.

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Hoc adhiberi potest describere algorithms ubi optimum et pessimum casibus

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sunt idem.

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Algorithms longitudine nervus, in quo fit mentio supra.

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Quod si ante differentia reponunt

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nos reponere chorda et obvius is postea in tempus constans.

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Quocumque numero

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in thesaurizas variabili sumus, puteus habeat considerare.

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Quod optimum sit, spectare

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longitudo fili invenire.

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Sic Ω (I) vel optimus-casu tempus constans.

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Pessimus casus est,

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longitudo fili, et invenies videamus.

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Ita, (I) quam si semper in peius.

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Quum causa optima pessima sunt idem re,

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Θ dici potest currere (I) est.

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>> In summa, habemus bonum vias ad rationis de codes efficientiam

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absque scire aliquid de verus-mundi tempus capiunt currere,

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multis extrinseco quod afficitur,

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quos possidet differentes hardware, software,

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aut speciali vestra code.

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Item R. de futuro sinit

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quando moli inputs crescit.

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>> Si curris in O (n) ² algorithm,

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aut peius, O (II ⁿ) algorithm,

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unus de ieiunas accrescens typos,

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youll realiter satus animadverto slowdown

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cum vos satus opus cum pluribus amounts of notitia.

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>> Ut 'asymptotici complexionem. Gratias.