The Pros And Cons Of The Turing Test
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The maximum likelihood estimate for the probability distribution of the experiment used to generate a frequency distribution. An mutable probdist where the probabilities may be easily modified. This simply copies an existing probdist, storing the probability values in a mutable dictionary and providing an update method. Update the probability for the given sample. This may cause the object to stop being the valid probability distribution - the user must ensure that they update the sample probabilities such that all samples have probabilities between 0 and 1 and that all probabilities sum to one.
A probability distribution for the outcomes of an experiment. A probability distribution specifies how likely it is that an experiment will have any given outcome. For example, a probability distribution could be used to predict the probability that a token in a document will have a given type. A ProbDist is often used to model the probability distribution of the experiment used to generate a frequency distribution. Return a randomly selected sample from this probability distribution.
The probability of returning each sample samp is equal to self. A mix-in class to associate probabilities with other classes trees, rules, etc. To use the ProbabilisticMixIn class, define a new class that derives from an existing class and from ProbabilisticMixIn. You will need to define a new constructor for the new class, which explicitly calls the constructors of both its parent classes. For example:. You should generally also redefine the string representation methods, the comparison methods, and the hashing method.
Return log p , where p is the probability associated with this object. SimpleGoodTuring ProbDist approximates from frequency to frequency of frequency into a linear line under log space by linear regression. Details of Simple Good-Turing algorithm can be found in:. Given a set of pair xi, yi , where the xi denotes the frequency and yi denotes the frequency of frequency, we want to minimize their square variation. E x and E y represent the mean of xi and yi. This function returns the total mass of probability transfers from the seen samples to the unseen samples.
Use simple linear regression to tune parameters self. A probability distribution that assigns equal probability to each sample in a given set; and a zero probability to all other samples. The Witten-Bell estimate of a probability distribution. This distribution allocates uniform probability mass to as yet unseen events by using the number of events that have only been seen once. This equates to the maximum likelihood estimate of a new type event occurring.
The remaining probability mass is discounted such that all probability estimates sum to one, yielding:. This module brings together a variety of NLTK functionality for text analysis, and provides simple, interactive interfaces. Functionality includes: concordancing, collocation discovery, regular expression search over tokenized strings, and distributional similarity. An index that can be used to look up the offset locations at which a given word occurs in a document. A list of the offset positions at which the given word occurs.
Print concordance lines given the query word. The context of a word is usually defined to be the words that occur in a fixed window around the word; but other definitions may also be used by providing a custom context function. Find contexts where the specified words can all appear; and return a frequency distribution mapping each context to the number of times that context was used. A wrapper around a sequence of simple string tokens, which is intended to support initial exploration of texts via the interactive console. If you wish to write a program which makes use of these analyses, then you should bypass the Text class, and use the appropriate analysis function or class directly instead. A Text is typically initialized from a given document or corpus.
Prints a concordance for word with the specified context window. Word matching is not case-sensitive. Generate a concordance for word with the specified context window. Produce a plot showing the distribution of the words through the text. Requires pylab to be installed. Find instances of the regular expression in the text. The text is a list of tokens, and a regexp pattern to match a single token must be surrounded by angle brackets.
Print random text, generated using a trigram language model. See also help nltk. If provided,. Distributional similarity: find other words which appear in the same contexts as the specified word; list most similar words first. A collection of texts, which can be loaded with list of texts, or with a corpus consisting of one or more texts, and which supports counting, concordancing, collocation discovery, etc. Initialize a TextCollection as follows:.
The number of texts in the corpus divided by the number of texts that the term appears in. If a term does not appear in the corpus, 0. A class that makes it easier to use regular expressions to search over tokenized strings. The tokenized string is converted to a string where tokens are marked with angle brackets — e. The regular expression passed to the findall method is modified to treat angle brackets as non-capturing parentheses, in addition to matching the token boundaries; and to have '. Return an iterator that returns the next field in a marker, value tuple, where marker and value are unicode strings if an encoding was specified in the fields method.
Otherwise they are non-unicode strings. If it is specified then the fields method returns unicode strings rather than non unicode strings. Same as the decode builtin string method. Ignored if encoding is None. Return an iterator that returns the next field in a marker, value tuple. Linebreaks and trailing white space are preserved except for the final newline in each field. Same as decode builtin method. Return a string with a standard format representation of the toolbox data in tree tree can be a toolbox database or a single record. Same as the encode builtin string method. Class for representing hierarchical language structures, such as syntax trees and morphological trees.
ImmutableTree , nltk. Convert a tree between different subtypes of Tree. Set the node label. This will only succeed the first time the node label is set, which should occur in ImmutableTree. A Tree that automatically maintains parent pointers for multi-parented trees. Each MultiParentedTree may have zero or more parents. In particular, subtrees may be shared. If a single MultiParentedTree is used as multiple children of the same parent, then that parent will appear multiple times in its parents method. Mixing tree implementations may result in incorrect parent pointers and in TypeError exceptions. A list of all left siblings of this tree, in any of its parent trees. A tree may be its own left sibling if it is used as multiple contiguous children of the same parent.
A tree may appear multiple times in this list if it is the left sibling of this tree with respect to multiple parents. Return a list of the indices where this tree occurs as a child of parent. If this child does not occur as a child of parent , then the empty list is returned. The following is always true:. The set of parents of this tree. If this tree has no parents, then parents is the empty set. A list of all right siblings of this tree, in any of its parent trees. A tree may be its own right sibling if it is used as multiple contiguous children of the same parent.
A tree may appear multiple times in this list if it is the right sibling of this tree with respect to multiple parents. The set of all roots of this tree. This set is formed by tracing all possible parent paths until trees with no parents are found. Return a list of all tree positions that can be used to reach this multi-parented tree starting from root. A Tree that automatically maintains parent pointers for single-parented trees.
Each ParentedTree may have at most one parent. In particular, subtrees may not be shared. Any attempt to reuse a single ParentedTree as a child of more than one parent or as multiple children of the same parent will cause a ValueError exception to be raised. The index of this tree in its parent. Note that ptree. The root of this tree. If ptree. The tree position of this tree, relative to the root of the tree. Tree , nltk. Bases: list. A Tree represents a hierarchical grouping of leaves and subtrees. For example, each constituent in a syntax tree is represented by a single Tree.
Tree positions are defined as follows:. The tree position specifies the Tree itself. Convert a tree into its Chomsky Normal Form CNF equivalent — Every subtree has either two non-terminals or one terminal as its children. Collapse subtrees with a single child ie. This is useful when working with algorithms that do not allow unary productions, and completely removing the unary productions would require loss of useful information.
The Tree is modified directly since it is passed by reference and no value is returned. Part-of-Speech tags since they are always unary productions. A tree corresponding to the list representation l. Read a bracketed tree string and return the resulting tree. Trees are represented as nested brackettings, such as:. They should have the following signature:. For example, these functions could be used to process nodes and leaves whose values should be some type other than string such as FeatStruct. By default, both nodes patterns are defined to match any sequence of non-whitespace non-bracket characters. This is useful for treebank trees, which sometimes contain an extra level of bracketing.
A tree corresponding to the string representation s. If this class method is called using a subclass of Tree, then it will return a tree of that type. The height of this tree. The tree position of the index -th leaf in this tree. This number is used to decide how far to indent subsequent lines. Returns a representation of the tree compatible with the LaTeX qtree package. For example, the following result was generated from a parse tree of the sentence The announcement astounded us :. For explanation of the arguments, see the documentation for nltk. Generate the productions that correspond to the non-terminal nodes of the tree.
Generate all the subtrees of this tree, optionally restricted to trees matching the filter function. The tree position of the lowest descendant of this tree that dominates self. Transforms a tree in Chomsky Normal Form back to its original structure branching greater than two. Parse a Sinica Treebank string and return a tree. Although many of these methods are technically grammar transformations ie.
Chomsky Norm Form , when working with treebanks it is much more natural to visualize these modifications in a tree structure. Hence, we will do all transformation directly to the tree itself. Transforming the tree directly also allows us to do parent annotation. A grammar can then be simply induced from the modified tree. It is well known that any grammar has a Chomsky Normal Form CNF equivalent grammar where CNF is defined by every production having either two non-terminals or one terminal on its right hand side.
When we have hierarchically structured data ie. In order to convert a tree into CNF, we simply need to ensure that every subtree has either two subtrees as children binarization , or one leaf node non-terminal. In order to binarize a subtree with more than two children, we must introduce artificial nodes. There are two popular methods to convert a tree into CNF: left factoring and right factoring. The following example demonstrates the difference between them. In addition to binarizing the tree, there are two standard modifications to node labels we can do in the same traversal: parent annotation and Markov order-N smoothing or sibling smoothing. The purpose of parent annotation is to refine the probabilities of productions by adding a small amount of context.
A natural generalization from parent annotation is to grandparent annotation and beyond. The tradeoff becomes accuracy gain vs. We must also keep in mind data sparcity issues. Markov smoothing combats data sparcity issues as well as decreasing computational requirements by limiting the number of children included in artificial nodes.
In practice, most people use an order 2 grammar. Annotation decisions can be thought about in the vertical direction parent, grandparent, etc and the horizontal direction number of siblings to keep. Parameters to the following functions specify these values. For more information see:. Collapse unary productions ie. This is useful when working with algorithms that do not allow unary productions, yet you do not wish to lose the parent information.
Traverse the nodes of a tree in depth-first order, discarding eventual cycles within the same branch, but keep duplicate paths in different branches. Return the line from the file with first word key. Searches through a sorted file using the binary search algorithm. Traverse the nodes of a tree in breadth-first order. No check for cycles. This function is a fast way to calculate binomial coefficients, commonly known as nCk, i. This is the scipy. Yield the edges of a graph in breadth-first order, discarding eventual cycles. Recursive function to indent an ElementTree. Run indent on elem and then output in the normal way.
Given a byte string, attempt to decode it. If unsuccessful it raises a UnicodeError. Return True if this function is run within idle. Tkinter programs that are run in idle should never call Tk. This function works by checking sys. If the user has modified sys. Wrap with list for a list version of this function. Return a string with markers surrounding the matched substrings. Search str for substrings matching regexp and wrap the matches with braces. This is convenient for learning about regular expressions.
If proxy is None then tries to set proxy from environment or system settings. Returns all possible skipgrams generated from a sequence of items, as an iterator. Skipgrams are ngrams that allows tokens to be skipped. Calculate the transitive closure of a directed graph, optionally the reflexive transitive closure. Output a dictionary representing a Minimum Spanning Tree MST of an unweighted graph, by traversing the nodes of a tree in breadth-first order, discarding eventual cycles.
Build a Minimum Spanning Tree MST of an unweighted graph, by traversing the nodes of a tree in breadth-first order, discarding eventual cycles. The mounting bracket of the Phoenix has been beefed up with Stainless Steel that is harder and more resistant to corrosion. Auto-Extreme Technology is an automated manufacturing process that sets new standards in the industry by allowing all soldering to be completed in a single pass.
This reduces thermal strain on components and avoids the use of harsh cleaning chemicals, resulting in less environmental impact, lower manufacturing power consumption, and a more reliable product overall. It allows you to tweak critical parameters including GPU core clocks, memory frequency, and voltage settings, with the option to monitor everything in real-time through a customizable on-screen display. Advanced fan control is also included along with many more features to help you get the most out of your graphics card. XSplit offers a premium streaming experience with in-game annotations and other advanced features. Enjoy a free license with the purchase of select ASUS graphics cards. See you online! We've partnered with wtfast to help you to play free from lag, latency issues, and lost packets.
With a 6-month subscription to the wtfast Gamers Private Network, you'll enjoy lower ping for a smoother, more fluid online gaming experience. Buy an ASUS graphics card - and don't be left waiting! Enjoy AAA games without the nuisance of screen tearing or stuttering. Capture and share videos, screenshots, and livestreams with friends, keep your GeForce drivers up to date, and easily optimize your in-game settings. This powerful tool lets you take professional-grade screenshots of your games. Now, you can record and share your most brilliant gaming experiences with super-resolution, degree, HDR, and stereoscopic capture modes. Dedicated GPU power accelerates the creative apps you use every day. Skip to content Accessibility help.
For Home. For Work. For Creators. For Students. For gamers who have a particularly good graphics card, there is a special Ultra mode for the graphics details in some games, which often also offers HD textures, i. Sometimes HD textures can also be optionally downloaded by the players first. Or private users offer HD textures if the respective game is moddable. A good example for the latter case is The Elder Scrolls: Skyrim, which now has a huge fan community as well as countless mods, many of which also refer to graphics and offer better or simply different textures. But even without additional downloads almost every game still offers the possibility to choose between quite good, average or rather bad texture quality, depending on what your PC can handle.
The connection between video RAM and textures should be clear now: in order for the objects to look realistic, many textures of high quality and high resolution must be used. A higher resolution in turn means that the texture also requires more memory than a texture with lower resolution. Since the texture should be available in the video RAM for smooth gaming, it also plays a role in how much video RAM the graphics card has. If there is too little Video RAM available, the textures have to be reloaded from the hard disk again and again — this can lead to a kind of data jam and a jerky game. The graphics card itself could already calculate the new image, but has to wait for the texture to be loaded into the VRAM, so that the game graphics falters.
For this reason it pays off if the graphics card has as much VRAM as possible — especially with a view to the future. In addition, some graphics detail modes require a minimum amount of VRAM to be able to play this mode. Especially for games that allow modifications of the game content, the mods that improve the graphical quality are especially popular. Here it can happen that you need much more VRAM than before. With downsampling, the image is calculated by the graphics card in a resolution that is significantly higher than the resolution of the monitor. Afterwards, the high-resolution image is downsampled to the resolution that matches the monitor — for most players this means Full-HD.
Advantage: the higher resolution allows more details to be calculated, which, by cleverly downscaling the image to normal Full-HD resolution, results in a slightly better overall picture than if the graphics card only calculates in Full-HD. The differences are not big, but depending on the game, they are quite visible. But of course downsampling requires much more graphics processing power and VRAM. You can find some information about downsampling in the article of our colleagues from PC Games Hardware from last year, which is still up to date and where you can find some sample images.
The demand for VRAM at higher details is growing from year to year. The graphics modes with extremely high-resolution textures often look only slightly better than the next lower graphics level in the running game — so you should be left in doubt, especially since the ultra details are rather a bonus with some games, with which the developers want to show what is possible at most. Currently, when buying a new graphics card, which should keep up with maximum details for a while, you should still look out for at least 4 gigabytes of graphics RAM, from a budget of Dollar four gigabytes.
Six gigabytes of graphics RAM as a requirement for the graphics card is something that is only available for very special texture packs that are usually only available via optional download. For example Middle Earth: Shadow of Mordor. Graphics cards over Dollar with more than eight gigabytes of VRAM should at most be seen as useful for gamers who can spend extremely high amounts of money on hardware to use special HD textures or even for especially high resolutions or downsampling.
Finally, we have compiled some current gaming graphic card series as purchase tips in a table, which are available in the shops with six GB VRAM. The cards are sorted by performance on the top of this page. Our CPU cooler test and…. Save my name, email, and website in this browser for the next time I comment. Best Price-Performance Ratio. Test Result. Test Result 9. Video Memory. Clock rate. Memory bandwidth. Value for money. Outstanding features and build quality Reasonably priced Efficient and overclockable Great performance at x Higher power consumption.
No ray tracing support.