The Center for Epidemiological Studies Depression Scale: Measurement and structural invariance across ratings of older adult men and women
- Authors: Gomez, Rapson , McLaren, Suzanne
- Date: 2015
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 75, no. (2015), p. 130-134
- Full Text: false
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- Description: The current study examined the measurement and structural invariance of the Center for Epidemiological Studies Depression Scale (CES-D; Radloff, 1977) across ratings provided by older adult men (. n=. 573) and women (. n=. 605). Ratings were modeled in terms of the original four-factor oblique model: a simple structure with correlated factors for Depressed Affect, Positive Affect, Somatic Symptoms, and Interpersonal Difficulties. Multiple-group confirmatory factor analysis supported full measurement and structural invariance, and no sex difference for the four latent factors. These findings indicate good support for measurement and structural invariance of CES-D ratings across older adult men and women. The psychometric and practical implications of the findings are discussed.
The personal construct and language: Toward a rehabilitation of Kelly's inner outlook
- Authors: Peck, Blake
- Date: 2015
- Type: Text , Journal article
- Relation: Theory and Psychology Vol. 25, no. 3 (2015), p. 259-273
- Full Text: false
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- Description: The core consideration with which George Kelly is concerned is distilled in his suggestion that the psychology of personal constructs represents an attempt to catch a glimpse of the person going about the business of being human. Whatever the business of being human is for Kelly, he is clear that he wishes to understand that business from the perspective of those who are going about it. To use Kelly’s words, he wants to take the perspective of the “inward outlook†and in so doing move away from the “outward inlook,†providing a radical rethink of the psychology that was contemporary of his time. This article will suggest that the unsophisticated way that Kelly dealt with language has implications for the theoretical carriage of this “inner outlook†and opens up Personal Construct Psychology to elaboration in the direction of a more sophisticated account of language. This article will culminate in a suggestion that Personal Construct Psychology make a more tight hermeneutic turn to Hermeneutic Constructivism. © The Author(s) 2015
A Case study illustrating therapist-assisted internet cognitive behavior therapy for depression
- Authors: Pugh, Nicole , Hadjistavropoulos, Heather , Klein, Britt , Austin, David
- Date: 2014
- Type: Text , Journal article
- Relation: Cognitive and Behavioral Practice Vol. 21, no. 1 (2014), p. 64-77
- Full Text: false
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- Description: Randomized controlled trials show that therapist-assisted Internet cognitive behavior therapy (ICBT) is efficacious in the treatment of depression. Given that this is a novel way of delivering cognitive behavior therapy, however, clinical service providers may have questions about how to provide therapist-assisted ICBT in clinical practice, particularly with respect to therapist assistance. To exemplify this approach, we present a case study of an older adult male who received 12 modules of therapist-assisted ICBT for depression over the course of 5. months. Highlights of the therapeutic exchanges that occurred over email are provided to illustrate the type of information clients may share with therapists and the nature of therapist assistance. Treatment progress was assessed via self-report questionnaires measuring depression, anxiety, and adjustment. Consistent with the research evidence, significant improvement was observed on all symptom measures at posttreatment. Satisfaction with the therapist-assisted ICBT program and a strong therapeutic alliance was also reported. The case will expand clinician understanding of therapist-assisted ICBT and may serve to stimulate clinician interest in the provision of therapist-assisted ICBT. Future research directions stemming from this case are presented. © 2013.
A critical examination of the reliability and validity of the SZTPI-15 in British, American and Australian samples
- Authors: McKay, Michael , Worrell, Frank , Temple, Elizabeth , Perry, John , Cole, Jon
- Date: 2014
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 69, no. (October 2014 2014), p. 168-172
- Full Text: false
- Reviewed:
- Description: As an individual difference variable assessing the extent to which attitudes towards past, present and future influence behavior, time perspective is a potentially useful construct. However, its development and utility has been compromised by measurement issues. Recently, a short form of the Zimbardo Time Perspective Inventory (ZTPI), the SZTPI-15 has been suggested to yield valid and reliable scores. Using three independent samples from America, Australia, and the United Kingdom, the present study tested the psychometric properties of SZPTI-15 scores. Confirmatory factor analyses did not support the 5-factor structure and internal consistency estimates for four of the subscales were low. Fit indices obtained from exploratory structural equation modeling were better, suggesting that permitting items to load on multiple factors improved model fit. Correlations with variables shown to be related to ZTPI factors broadly supported the concurrent validity of the SZTPI-15. Results suggest that further psychometric examination of SZTPI-15 scores is required.
- Description: C1
A new loss function for robust classification
- Authors: Zhao, Lei , Mammadov, Musa , Yearwood, John
- Date: 2014
- Type: Text , Journal article
- Relation: Intelligent Data Analysis Vol. 18, no. 4 (2014), p. 697-715
- Full Text: false
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- Description: Loss function plays an important role in data classification. Manyloss functions have been proposed and applied to differentclassification problems. This paper proposes a new so called thesmoothed 0-1 loss function, that could be considered as anapproximation of the classical 0-1 loss function. Due to thenon-convexity property of the proposed loss function, globaloptimization methods are required to solve the correspondingoptimization problems. Together with the proposed loss function, wecompare the performance of several existing loss functions in theclassification of noisy data sets. In this comparison, differentoptimization problems are considered in regards to the convexity andsmoothness of different loss functions. The experimental resultsshow that the proposed smoothed 0-1 loss function works better ondata sets with noisy labels, noisy features, and outliers. © 2014 - IOS Press and the authors. All rights reserved.
Attention-Deficit/Hyperactivity Disorder symptoms in an adult sample: Associations with Rothbart's temperament dimensions
- Authors: Gomez, Rapson , Kyriakides, Chantelle , Devlin, Elaine
- Date: 2014
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 60, no. (2014), p. 73-78
- Full Text: false
- Description: Relationships between Rothbart's 13 temperament sub-dimensions and the Attention-Deficit/Hyperactivity Disorder (ADHD) factors for the 2-factor model [inattention (IA) and hyperactivity/impulsivity (HI) domains] and the bifactor model (general ADHD, and specific factors for IA and HI) were examined in 267 adults from the general population. Regression analyses revealed that (1) both the IA and HI factors in the 2-factor model and the general ADHD factor in the bifactor model were predicted positively by sad, discomfort and associative sensitivity, and negatively by activation control, (2) the HI domain factor in the 2-factor model was also predicted negatively by inhibitory control, (3) the specific IA factor in the bifactor model was predicted negatively by activation control and attention control, and (4) the HI specific factor in the bifactor model was predicted negatively by inhibitory control and positively by sociability. These theoretical and clinical implications of the findings are discussed. © 2014.
Can you tickle yourself if you swap bodies with someone else?
- Authors: Van Doorn, George , Hohwy, Jakob , Symmons, Mark
- Date: 2014
- Type: Text , Journal article
- Relation: Consciousness and Cognition Vol. 23, no. (2014), p. 1-11
- Full Text: false
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- Description: The effect of the body transfer illusion on the perceived strength of self- and externally-generated "tickle" sensations was investigated. As expected, externally generated movement produced significantly higher ratings of tickliness than those associated with self-generated movements. Surprisingly, the body transfer illusion had no influence on the ratings of tickliness, suggesting that highly surprising, and therefore hard to predict, experiences of body image and first-person perspective do not abolish the attenuation of tickle sensations. In addition, evidence was found that a version of the rubber hand illusion exists within the body transfer illusion. We situate our findings within the larger debate over sensory attenuation: (1) there is an attenuation of prediction errors that depends upon the context in which sensory input is predicted (i.e., efference copy), and (2) sensory attenuation is a necessary consequence of self-generated movement irrespective of context (i.e., active inference). The results support the notion of active inference.
Depression anxiety stress scales-21 : Factor structure and test-retest invariance, and temporal stability and uniqueness of latent factors in older adults
- Authors: Gomez, Rapson , Summers, Mathew , Summers, Avril , Wolf, Anna , Summers, Jeff
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Psychopathology and Behavioral Assessment Vol. 36, no. 2 (2014), p. 308-317
- Full Text: false
- Reviewed:
- Description: This study examined the factor structure and test-retest invariance, and temporal stability and uniqueness of the latent factors (depression, anxiety, and stress) of the Depression Anxiety Stress Scales-21 (DASS-21; Lovibond & Lovibond, 1995) in group a of 269 older adults (age ranging from 60 to 85 years) from the general community. Participants completed the DASS-21 twice, 3 months apart. Confirmatory factor analysis (CFA) of their ratings at Time 1 indicated support for the original 3-factor oblique model (factors for depression, anxiety, and stress). Additional analyses showed support for test-retest invariance for both the measurement (configural, metric and thresholds) and structural (variances and covariances) components of this model. Results also indicated temporal stability and uniqueness of the latent factors. The practical, theoretical, research and clinical implications of the findings are discussed. © 2013 Springer Science+Business Media.
Impulsive control for synchronizing delayed discrete complex networks with switching topology
- Authors: Li, Chaojie , Gao, David , Liu, Chao , Chen, Guo
- Date: 2014
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 24, no. 1 (2014), p. 59-68
- Full Text: false
- Reviewed:
- Description: In this paper, global exponential synchronization of a class of discrete delayed complex networks with switching topology has been investigated by using Lyapunov-Ruzimiki method. The impulsive scheme is designed to work at the time instant of switching occurrence. A time-varying delay-dependent criterion for impulsive synchronization is given to ensure the delayed discrete complex networks switching topology tending to a synchronous state. Furthermore, a numerical simulation is given to illustrate the effectiveness of main results © 2013 The Author(s).
The future is here : A review of foresight systems in anxiety and depression
- Authors: Miloyan, Beyon , Pachana, Nancy , Suddendorf, Thomas
- Date: 2014
- Type: Text , Journal article
- Relation: Cognition and Emotion Vol. 28, no. 5 (2014), p. 795-810
- Full Text: false
- Reviewed:
- Description: Cognitive models of anxiety and depression have long suggested a central role for future-oriented thinking in these disorders. Experimental studies suggest that anxiety and depression are characterised by distinct future-oriented thinking profiles, and that these profiles are markedly different from those of asymptomatic adults. In this paper, we review these profiles and propose two explanatory models marked by two different neurocognitive systems. The Reconstructive Memory Model emphasises a role for emotionally driven learning and retrieval in episodic foresight (i.e., the construction of future-oriented scenarios), and the Valuation Model proposes that an overweighing of risk and uncertainty estimates can be invoked to explain the future-oriented thought patterns. We consider the effectiveness of interventions aimed at altering such thought patterns. We suggest that future research aimed at elucidating the neurobiological underpinnings of future-oriented thinking in anxiety and depression can play an important role in advancing development of effective biological and psychosocial interventions for these disorders.
Unique associations of reinforcement sensitivity theory dimensions with social interaction anxiety and social observation anxiety
- Authors: Ly, Corina , Gomez, Rapson
- Date: 2014
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 60, no. (2014), p. 20-24
- Full Text: false
- Reviewed:
- Description: Relationships between Rothbart’s 13 temperament sub-dimensions and the Attention-Deficit/Hyperactivity Disorder (ADHD) factors for the 2-factor model [inattention (IA) and hyperactivity/impulsivity (HI) domains] and the bifactor model (general ADHD, and specific factors for IA and HI) were examined in 267 adults from the general population. Regression analyses revealed that (1) both the IA and HI factors in the 2-factor model and the general ADHD factor in the bifactor model were predicted positively by sad, discomfort and associative sensitivity, and negatively by activation control, (2) the HI domain factor in the 2-factor model was also predicted negatively by inhibitory control, (3) the specific IA factor in the bifactor model was predicted negatively by activation control and attention control, and (4) the HI specific factor in the bifactor model was predicted negatively by inhibitory control and positively by sociability. These theoretical and clinical implications of the findings are discussed. ADHD
Backbreak prediction in the Chadormalu iron mine using artificial neural network
- Authors: Monjezi, Masoud , Ahmadi, Zabiholla , Yazdian-Varjani, Ali , Khandelwal, Manoj
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 23, no. 3-4 (2013), p. 1101-1107
- Full Text: false
- Reviewed:
- Description: Backbreak is one of the unfavorable blasting results, which can be defined as the unwanted rock breakage behind the last row of blast holes. Blast pattern parameters, like stemming, burden, delay timing, stiffness ratio (bench height/burden) and rock mass conditions (e.g., geo-mechanical properties and joints), are effective in backbreak intensity. Till date, with the exception of some qualitative guidelines, no specific method has been developed for predicting the phenomenon. In this paper, an effort has been made to apply artificial neural networks (ANNs) for predicting backbreak in the blasting operation of the Chadormalu iron mine (Iran). Number of ANN models with different hidden layers and neurons were tried, and it was found that a network with architecture 10-7-7-1 is the optimum model. A comparative study also approved the superiority of the ANN modeling over the conventional regression analysis. Mean square error (MSE), variance account for (VAF) and coefficient of determination (R 2) between measured and predicted backbreak for the ANN model were calculated and found 89.46 %, 0.714 and 90.02 %, respectively. Also, for the regression model, MSE, VAF and R 2 were computed and found 66.93 %, 1.46 and 68.10 %, respectively. Sensitivity analysis was also carried out to find out the influence of each input parameter on backbreak results, and it was revealed that burden is the most influencing parameter on the backbreak, whereas water content is the least effective parameter in this regard. © 2012 Springer-Verlag London Limited.
Big five personality traits, job satisfaction and subjective wellbeing in China
- Authors: Zhai, Qingguo , Willis, Mike , O'Shea, Bob , Zhai, Yubo , Yang, Yuwen
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Psychology Vol. 48, no. 6 (December 2013), p. 1099-1108
- Full Text: false
- Reviewed:
- Description: This paper examines the effect of the Big Five personality traits on job satisfaction and subjective wellbeing (SWB). The paper also examines the mediating role of job satisfaction on the Big Five-SWB relationship. Data were collected from a sample of 818 urban employees from five Chinese cities: Harbin, Changchun, Shenyang, Dalian, and Fushun. All the study variables were measured with well-established multi-item scales that have been validated both in English-speaking populations and in China. The study found only extraversion to have an effect on job satisfaction, suggesting that there could be cultural difference in the relationships between the Big Five and job satisfaction in China and in the West. The study found that three factors in the Big Fiveextraversion, conscientiousness, and neuroticismhave an effect on SWB. This finding is similar to findings in the West, suggesting convergence in the relationship between the Big Five and SWB in different cultural contexts. The research found that only the relationship between extraversion and SWB is partially mediated by job satisfaction, implying that the effect of the Big Five on SWB is mainly direct, rather than indirect via job satisfaction. The study also found that extraversion was the strongest predictor of both job satisfaction and SWB. This finding implies that extraversion could be more important than other factors in the Big Five in predicting job satisfaction and SWB in a high collectivism and high power distance country such as China. The research findings are discussed in the Chinese cultural context. The study also offers suggestions on the directions for future research.
- Description: C1
Depression Anxiety Stress Scales : Factor structure and differential item functioning across women and men
- Authors: Gomez, Rapson
- Date: 2013
- Type: Text , Journal article
- Relation: Personality and Individual Differences Vol. 54, no. 6 (2013), p. 687-691
- Full Text: false
- Reviewed:
- Description: This study examined the factor structure, and differential item functioning of the Depression Anxiety Stress Scales (DASS; Lovibond & Lovibond, 1995) across sex. The DASS was completed by 201 women and 165 men from the general community. Confirmatory factor analysis (CFA) indicated support for the original 3-factor oblique model (factors for depression, anxiety and stress). There was however more support for a bifactor model, with four orthogonal factors: a general factor on which all the depression, anxiety and stress items load, and specific independent factors for depression, anxiety and stress items. None of the DASS items showed DIF. The practical, theoretical, research and clinical implications of the findings are discussed. © 2012 Elsevier Ltd.
Efficient nonlinear classification via low-rank regularised least squares
- Authors: Fu, Zhouyu , Lu, Guojun , Ting, Kaiming , Zhang, Dengsheng
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 22, no. 7-8(2013), p. 1279-1289
- Full Text: false
- Reviewed:
- Description: We revisit the classical technique of regularised least squares (RLS) for nonlinear classification in this paper. Specifically, we focus on a low-rank formulation of the RLS, which has linear time complexity in the size of data set only, independent of both the number of classes and number of features. This makes low-rank RLS particularly suitable for problems with large data and moderate feature dimensions. Moreover, we have proposed a general theorem for obtaining the closed-form estimation of prediction values on a holdout validation set given the low-rank RLS classifier trained on the whole training data. It is thus possible to obtain an error estimate for each parameter setting without retraining and greatly accelerate the process of cross-validation for parameter selection. Experimental results on several large-scale benchmark data sets have shown that low-rank RLS achieves comparable classification performance while being much more efficient than standard kernel SVM for nonlinear classification. The improvement in efficiency is more evident for data sets with higher dimensions.
Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network
- Authors: Monjezi, Masoud , Hasanipanah, Mahdi , Khandelwal, Manoj
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 22, no. 7-8 (2013), p. 1637-1643
- Full Text: false
- Reviewed:
- Description: The purpose of this article is to evaluate and predict blast-induced ground vibration at Shur River Dam in Iran using different empirical vibration predictors and artificial neural network (ANN) model. Ground vibration is a seismic wave that spreads out from the blasthole when explosive charge is detonated in a confined manner. Ground vibrations were recorded and monitored in and around the Shur River Dam, Iran, at different vulnerable and strategic locations. A total of 20 blast vibration records were monitored, out of which 16 data sets were used for training of the ANN model as well as determining site constants of various vibration predictors. The rest of the 4 blast vibration data sets were used for the validation and comparison of the result of ANN and different empirical predictors. Performances of the different predictor models were assessed using standard statistical evaluation criteria. Finally, it was found that the ANN model is more accurate as compared to the various empirical models available. As such, a high conformity (R 2 = 0.927) was observed between the measured and predicted peak particle velocity by the developed ANN model. © 2012 Springer-Verlag London Limited.
Evaluation of effect of blast design parameters on flyrock using artificial neural networks
- Authors: Monjezi, Masoud , Mehrdanesh, Amirhossein , Malek, Alaeddin , Khandelwal, Manoj
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 23, no. 2 (2013), p. 349-356
- Full Text: false
- Reviewed:
- Description: Flyrock, the propelled rock fragments beyond a specific limit, can be considered as one of the most crucial and hazardous events in the open pit blasting operations. Involvement of various effective parameters has made the problem so complicated, and the available empirical methods are not proficient to predict the flyrock. To achieve more accurate results, employment of new approaches, such as artificial neural network (ANN) can be very helpful. In this paper, an attempt has been made to apply the ANN method to predict the flyrock in the blasting operations of Sungun copper mine, Iran. Number of ANN models was tried using various permutation and combinations, and it was observed that a model trained with back-propagation algorithm having 9-5-2-1 architecture is the best optimum. Flyrock were also computed from various available empirical models suggested by Lundborg. Statistical modeling has also been done to compare the prediction capability of ANN over other methods. Comparison of the results showed absolute superiority of the ANN modeling over the empirical as well as statistical models. Sensitivity analysis was also performed to identify the most influential inputs on the output results. It was observed that powder factor, hole diameter, stemming and charge per delay are the most effective parameters on the flyrock. © 2012 Springer-Verlag London Limited.
Fitting a bionic eye to the body: how haptics can help
- Authors: Van Doorn, George , Richardson, Barry , Wuillemin, Dianne
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Autonomous and Adaptive Communications Systems Vol. 6, no. 4 (2013), p. 377-390
- Full Text: false
- Reviewed:
- Description: The function of any visual prosthetic will be to generate patterned stimulation of the visual cortex arising from either direct stimulation (e.g. using cortical implants) or more peripheral inputs (e.g. an artificial retina). Direct cortical stimulation may result in patterns containing relatively few elements (say 10-100) while an artificial retina may deliver more complex patterns. We propose that regardless of the site of intervention, a tactile copy of the input, delivered to the skin at the same time as it is sent to the visual cortex, will offer significant advantages, especially during early stages of testing and development in which the user must 'make sense' of the novel input. The advantages of such a display include: (1) exploitation of multisensory processes such as cross-calibration, learning to discriminate sub-threshold stimuli and perceptual redundancy, (2) a means of measuring strengths and weaknesses of the prosthetic's visual input and evaluation of improvements and (3) a way of quickly adapting the congenitally- or late-blind user to the prosthetic.
Flow and Telepresence contributing to Internet Abuse : Differences according to gender and age
- Authors: Stavropoulos, Vasileios , Alexandraki, Kyriaki , Motti-Stefanidi, Frosso
- Date: 2013
- Type: Text , Journal article
- Relation: Computers in Human Behavior Vol. 29, no. 5 (2013), p. 1941-1948
- Full Text: false
- Reviewed:
- Description: Flow describes immersive tendencies to Internet activities, and Telepresence defines the level one is absorbed in his virtual environment. The aim of this study was twofold: (a) to test whether and how Flow and Telepresence may contribute to Internet Abuse and (b) to examine group differences in Internet Abuse, Flow and Telepresence according to gender and age among adolescents. The sample consisted of 1609 adolescents, with a mean age of 16 years old. Internet Abuse was assessed with the Internet Addiction Test (Young, 1998), Flow with the Flow Questionnaire (Chen, Wigand, & Nilan, 1999) and Telepresence with the Presence II questionnaire (Witmer & Singer, 1998). Findings revealed that Flow and Telepresence were related with Internet Abuse with Telepresence positively moderating the effect of Flow. Considering group differences, males were at higher risk of Internet Abuse and were more likely to experience Flow and Telepresence, while older adolescents scored higher only in Telepresence. © 2013 Elsevier Ltd. All rights reserved.
Local models - the key to boosting stable learners successfully
- Authors: Ting, Kaiming , Zhu, Lian , Wells, Jonathan
- Date: 2013
- Type: Text , Journal article
- Relation: Computational Intelligence Vol. 29, no. 2 (2013), p. 331-356
- Full Text: false
- Reviewed:
- Description: Boosting has been shown to improve the predictive performance of unstable learners such as decision trees, but not of stable learners like Support Vector Machines (SVM), k-nearest neighbours and Naive Bayes classifiers. In addition to the model stability problem, the high time complexity of some stable learners such as SVM prohibits them from generating multiple models to form an ensemble for large data sets. This paper introduces a simple method that not only enables Boosting to improve the predictive performance of stable learners, but also significantly reduces the computational time to generate an ensemble of stable learners such as SVM for large data sets that would otherwise be infeasible. The method proposes to build local models, instead of global models; and it is the first method, to the best of our knowledge, to solve the two problems in Boosting stable learners at the same time. We implement the method by using a decision tree to define local regions and build a local model for each local region. We show that this implementation of the proposed method enables successful Boosting of three types of stable learners: SVM, k-nearest neighbours and Naive Bayes classifiers.
- Description: Boosting has been shown to improve the predictive performance of unstable learners such as decision trees, but not of stable learners like Support Vector Machines (SVM), k-nearest neighbors and Naive Bayes classifiers. In addition to the model stability problem, the high time complexity of some stable learners such as SVM prohibits them from generating multiple models to form an ensemble for large data sets. This paper introduces a simple method that not only enables Boosting to improve the predictive performance of stable learners, but also significantly reduces the computational time to generate an ensemble of stable learners such as SVM for large data sets that would otherwise be infeasible. The method proposes to build local models, instead of global models; and it is the first method, to the best of our knowledge, to solve the two problems in Boosting stable learners at the same time. We implement the method by using a decision tree to define local regions and build a local model for each local region. We show that this implementation of the proposed method enables successful Boosting of three types of stable learners: SVM, k-nearest neighbors and Naive Bayes classifiers.