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where we de ne par ents(X i ) to be the set of immediate predecessors of X i in the network. The probabilities p(X i = xi | parents(X i ) and p(X i = xi | parents(X i ) are the probabilities that have been speci ed in the probability table associated with the node for X i . How does learning take place in a Bayesian network When the structure of the network is known and the eld values have all been observed, learning in Bayesian nets is straightforward. The local (node-speci c) probability tables are fully speci ed, and any joint, conditional, prior, or posterior probability desired may be calculated. However, when some of the eld values are hidden or unknown, we need to turn to other methods, with the goal of lling in all the entries in the local probability distribution table. Russell et al. [6] suggest a gradient descent method for learning in Bayesian networks. In this paradigm, the unknown entries in the probability distribution tables are considered to be unknown weights, and gradient descent methods, analogous to the neural network learning case (e.g., Larose [4, Chap. 7] and Mitchell [2, Chap. 4], can be applied to nd the optimal set of weights (probability values) given the data.

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192.168.016.053.64148-216.239.063.104.00080: GET / HTTP/1.1 Host: www.google.it Cookie:PREF=ID=5f2f91cd13521ebf:LD=it:TM=1105895484:LM=1105895 485:S=J4G_HJAk1i5fY0Ip 216.239.063.104.00080-192.168.016.053.64148: HTTP/1.1 200 OK Cache-Control: private

When you have nished tweaking the System Con guration Utility, click the Apply button. Click the OK button. A message alerts you that you must restart your computer for the changes to take effect. Click the Restart button.Your computer automatically shuts down and reboots. When you return to Windows, a message alerts you that you have just used the System Con guration Utility to change the way Windows starts. Put a checkmark in the box labeled Don t show this message or launch the system con guration utility when Windows starts. Click the OK button.

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COMMON THEMES From a health psychology perspective, several important themes emerge that concern the shared characteristics of alternative and complementary treatments in the context of an expanded mind/body rubric. These include: 1. A biopsychosocial model, which incorporates biological, immunological, psychological, spiritual, interpersonal, and environmental variables, characterizes an underlying mind/ body philosophy of most complementary and alternative approaches. Psychological wellness is viewed as a critical component of health regarding most of these therapeutic systems. Many psychological interventions, such as cognitive-behavioral therapy, group therapy, and hypnosis, may provide strategies that increase psychological well-being and decrease distress. 2. A holistic, individualized case assessment approach is a common method of diagnosis and treatment. Although each healing approach may vary in the methodology, such as use of the interview, physical exam techniques, or tests that are administered, there is a marked tendency to design treatment speci c to the individual case formulation rather than rely on a standard prescription or dosage strategy. 3. The underlying philosophy on which many complementary and alternative interventions are based view health as a state of harmony and energy balance, wherein the physical, emotional, mental, and spiritual aspects of energy are all given signi cant weight and seen as interrelated. 4. Treatment ef cacy is most often associated with stressrelated disorders and those diseases that have been etiologically linked to cognition, behavior, and lifestyle. This covers a wide range of what have been historically considered medical disorders, such as cardiac problems, diabetes, immune functioning disorders, asthma, pain syndromes, and gastrointestinal disorders.

Defense mechanisms, 119, 120 Deficiency-motivated, 129 Degenerative diseases, 346 347, 348 349 Degrees (PhD or PsyD), 10, 484 485 See also Education and training DeLeon, Patrick H.

, 3 4 Delis-Kaplin Executive Function System (D-KEFS), 231 Dementia, 346, 347, 348 Dementia praecox, 40 Denial, 119, 120 Depression: case studies, 187 188, 243, 248, 249, 347, 357 example of patient seeking psychotherapy, 266 267 medication, 288 multiple causes, 180 older adults, 351 outcome study, 307 women and, 281 282 Descartes, Ren , 39 Diagnostic and Statistical Manual of Mental Disorders (DSM), 190 193 anorexia nervosa, 193 diagnostic categories, and examples, 191 examples of DSM-IV diagnoses for three children, 194 panic attack, 78 Diagnostic interview, 190 193 Diagnostic Interview Schedule (DIS), 182 Dialectical behavior therapy (DBT), 127 Diathesis-stress perspective, 155 157 Differentiation, 132 Digit span (WAIS subtest description), 219 Digit-symbol coding (WAIS subtest description), 219 Diplomate, 455, 494 495 Disabilities, and Americans with Disabilities Act (ADA), 336 Discriminant validity, 182 Disengagement, 131, 132 Dismantling treatment strategies (treatment outcome research), 95 Disorders, 191 Displacement, 120 Dissociative disorders, 191, 467 468 Diversity.

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