AI Artificial Intelligence. Though relevant to, AI is not just about robots. It is firstly about the
mathematization of reasoning based on data especially the modern large data set now available through computer and communications technology. cf (Korb and Nicholson, 2011) which despite its name is about BN directed data collection and manipulation, not about SF style robots.
AIC Akaike Information Criterion score,
ASP/AS Activated Sludge Process/Activated Sludge (treatment)
Assessment (Bayesian)
(As used here) Probability assessment is the process of humans determining the probabilistic or deterministic relationships between nodes and their parents (usually in the form of
conditional probability tables) after all the nodes and the link structure have been created. Alternatively, they can be determined automatically by some learning procedure.
AUC Area Under the Curve for the receiver operating characteristic curve
BAN Bayesian network augmented naïve Bayes
BN A Bayes net (also known as a belief net) is composed of a set of nodes representing variables
of interest, connected by links to indicate dependencies, and containing information about the relationships between the nodes (often in the form of conditional probabilities). Usages include prediction, diagnosis, probabilistic modelling, learning from data and forming a basis for building decision nets.
BN/BBN Bayesian Belief Network – we have standardized on ‘BN’ but it is essential to not forget the
involvement of ‘Belief’ in the construction of BNs and the subtle traps it lays.
Belief The belief of a node is the set of probabilities (one for each of its possible states), taking into account the currently entered findings by using the knowledge encoded in the Bayes net. Technically, it is the marginal posterior probability distribution of the node, given the findings and the BN model. Sometimes the plural form “beliefs” is used to mean each of the probabilities in the set.
Belief updating Belief updating is the process of finding new beliefs for the nodes of a BN to account for the findings that are currently known. It is a form of probabilistic inference. During belief updating the BN model (in particular, the conditional probability tables between the nodes) is not modified at all; for that probability revision is used.
ca Circa about = approximately
Case A case is a set of findings that go together to provide information on one object, event, history,
person, or other thing.
cf. Compare for example
Chance node A chance node is a nature node whose relationship to its parents is probabilistic (i.e. not deterministic). If its parents’ values are all known, and there is no further information, then its value can only be inferred as a probability distribution over possible values. Compare with deterministic node.
Child node BNs are directional. If there is a link going from node A to node B, then B is said to be a child node of A. Some people refer to it as a direct successor.
Conditional
probability The conditional probability of an event is the probability of the event occurring under certain given conditions.
COPC Contaminant of Potential Concern. Typically pathogens and toxic or carcinogenic chemicals
which may be present in recycled water.
CPT CPT is an abbreviation for conditional probability table (also known as “link matrix”), which is
the contingency table of conditional probabilities stored at each node, containing the
probabilities of the node given each configuration of parent values. Sometimes CPT is used to refer to the deterministic function table of a node, since the node's conditional probabilities can easily be found from that. It is a form of node relation, so you use the table dialog box to change or view it.
.CSV File format standing for Comma Separated Values. These are a standard data storage file
format suitable for use by many software packages including Excel, Neticatm and WEKA.
DAG Directed Acyclic Graph
Decision net If decision nodes (representing variables that can be controlled) and utility nodes (representing variables to be optimized) are added to a BN, then a decision net (also known as an “influence diagram”) is formed.
Decision node A decision node is a node in a decision net which represents a variable (or choice) under the control of the decision maker. When the net is solved, a decision rule is found for the node
which optimizes the expected utility (EU). Decision nodes are normally drawn as rectangles (without rounded corners).
Decision theory Decision theory is a normative theory which indicates how a single agent should best make decisions to maximize his expected utility (EU). It considers sequences of decisions, what information the agent will have when he makes the decisions, uncertainties in the beliefs of the agent, and complex probabilistic interactions in the environment in which the agent is
operating. Deterministic
node A deterministic node is a nature node whose relationship with its parents is given as a function of the parent values (i.e. deterministic rather than probabilistic). If the parent values are all known, its value can be determined with certainty. Compare with chance node.
Entering findings When a BN is applied to a particular situation, or case, then the known information about that case is entered into the BN by assigning values (called "findings", or "evidence") to the known variables (i.e. nodes), and that process is known as entering findings into the nodes. Entering a finding into a particular node does not retract existing findings at that node or other nodes (but for convenience, at least in Neticatm applications, if the new finding for a node directly
contradicts a previously entered finding for that node, the previous finding will be retracted first).
Expected value The expected value (also known as mean value) is not the value you “expect” to see, and usually it isn’t even the value most likely to occur. This term, from probability theory, means the average value that will occur, where the average is weighted by the probability of
occurrence. For example if a value will be 3 with probability 0.2 and 9 with probability 0.8, then the expected value is (0.2 x 3) + (0.8 x 9) = 7.8.
Finding A finding (also known as “evidence”) is a value for one of the nodes (i.e. variables) of a BN
when it is applied to a particular situation.
FNR False negative rate
FPR False positive rate
Function table When the relationship between a node and its parents is deterministic, rather than probabilistic, then instead of a CPT a node may have function table, in which each row corresponds to a configuration of parent values, and the row provides a single output value for the child node. If a function table is converted to a CPT, then each row of the resulting CPT will consist only of zeroes, with a single 1 (or 100%) positioned at the state that was the function table's value for that row.
GUI Graphical User Interface
IDEA Intermittently Decanted Extended Aeration
Informational link Any link entering a decision node is known as an informational link, and indicates that the decision maker will know the value of the parent node when he must make that decision.
KS Kappa statistic
Leaf node A leaf node is a node with no children.
Link A link (also known as an “arc” or an “edge”) is a connection between two nodes indicating
dependence, and is usually drawn as a line with an arrow at one end.
LL Log-Likelihood score
LRV Log10 Reduction Value. Other acronyms used are DEC and DR for Decimal reduction. This
value describes extent to which a process of barrier reduces a contaminant level. It is useful because the reductions on microbial numbers typically desired are quantified in logarithms. It is useful as for most purposes an LRV of 1 implies a 1 log risk reduction as well.
Nature node A nature node in a BN represents some variable of interest. It may also appear in a decision
net in which case it is a variable that cannot be directly controlled by the decision maker (i.e. it is determined by nature). If a nature node has a functional relationship with its parents, it is called a deterministic node, whereas if the relationship is probabilistic, it is called a chance node. The characteristic shape for a nature node is an ellipse, or a rectangle with rounded corners.
NB Naïve BN
Net In Neticatm documentation, the word net is used to mean a BN or a decision net.
Neticatm Neticatm is a program created by Norsys for working with BNs and decision nets.
Node A node is a component of a BN or decision net used to represent a variable (i.e. scalar
quantity) of interest, and in Neticatm is usually drawn as a rectangle, rounded rectangle, circle
or flattened hexagon.
Node relationship A node relationship, or node relation for short, is the relationship between a node and its parents. It may provide the value of the node as a function of its parents’ values, or it may provide a probability distribution for the node depending on its parents’ values. It is often
expressed as a CPT in which case it can be viewed or edited using the table dialog box. Alternately, it may be expressed as a probabilistic or deterministic equation. No-forgetting links If a decision maker remembers the decisions they made at an earlier time, and also the
knowledge they had available at that time, then in his decision net there will be informational links going from earlier decision nodes and their parents, to later decision nodes. These are called no-forgetting links.
Outcome The outcome is the result of an event, or series of events, that could have turned out in one of
several ways.
PA Prediction Accuracy
Parent node If there is a link going from node A to node B, then A is said to be a parent node of B. Some people refer to it as a “direct predecessor”.
Probabilistic
inference Probabilistic inference is the process of calculating new beliefs for a set of variables, given some findings. Technically speaking, it is the process of finding a posterior distribution, given a prior distribution, a model and some observations.
Root node A root node is a node with no parents. See also leaf node.
SNB Semi-Naïve Bayesian Network
States A discrete variable can take on one of several values, and these values are called states. For
example the states may be “female, male”, or they might be “US, Europe, Japan, China”, or “True, False”. With Neticatm you can just let the states of a node be numbered, but usually you
give them meaningful names.
TAN Tree Augmented naïve Bayes
TNR True negative rate
TPR True positive rate
User reports A Neticatm mechanism which displays customized information pertaining to a node, group of nodes, or to an entire net. The user report could be as simple as a text message giving a more detailed description of what a node means. Or it could be more complex, such as the current belief probabilities of the nodes, or a sensitivity analysis of the net.
Utility node A utility node (also known as a “value node”) is a node in a decision net whose expected value is to be maximized while searching for the best decision rule for each of the decision nodes. It is usually drawn as a flattened hexagon or a diamond.
WEKA Waikato Environment for Knowledge Analysis